{"as_of":"2026-08-11T10:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:820883173c1859cad963f45c3ad09210cee62e4c96f77b5eeecb9850a4608f40","coverage":[{"denominator":94,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":94,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-16T15:27:04.228144Z","state":"measured"},{"denominator":143,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":143,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":49,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:17:20.613684Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T07:26:54.458175Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2505.22095","last_updated":"2026-04-06T12:52:40Z","snapshot_observed_at":"2026-08-02T15:44:17.473900Z","submitted_at":"2025-05-28T08:17:57Z","title":"Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-19T13:50:30.090068Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2505.22095"},"observation_digest":"sha256:a02ccc2285831c33e3fdaf1447ac923def744fbcb22bf995568571f63a8f1f06","observation_id":"f5e920ef-b2ce-4b2c-b9bb-2e4c2807f857","resolution":{"observed_at":"2026-05-19T13:52:19.930346Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-06T16:33:59.034226Z","title":"Mmsearch-r1: Incentivizing lmms to search","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.13348","last_updated":"2025-07-17T17:59:55Z","snapshot_observed_at":"2026-08-10T11:05:10.491989Z","submitted_at":"2025-07-17T17:59:55Z","title":"VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T16:33:59.034226Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2507.13348"},"observation_digest":"sha256:52692eaff71103dddf1b00a980a8c219c20c51abdbbca9d5cecafb6956fdfbe4","observation_id":"4c5f3fec-36e2-407a-b268-45f443a9ed73","resolution":{"observed_at":"2026-08-06T16:33:59.034226Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-05T22:01:26.017258Z","title":"arXiv preprint arXiv:2506.20670 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.07683","last_updated":"2026-06-29T02:15:03Z","snapshot_observed_at":"2026-08-06T21:12:13.753696Z","submitted_at":"2025-08-11T06:59:32Z","title":"TAR: Temporal Anchor-Constrained Reasoning for Video Temporal Grounding","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T22:01:26.017258Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2508.07683"},"observation_digest":"sha256:9c369d33af122c4f09ca9cb8f9edf6a97b2732396b6bc39e6ffefd99db89cc4c","observation_id":"a788f0ba-d0a3-40a2-920b-fbbf6831c059","resolution":{"observed_at":"2026-08-05T22:01:26.017258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-05T20:18:58.629661Z","title":"Mmsearch-r1: Incentivizing lmms to search","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.13186","last_updated":"2025-08-14T13:46:47Z","snapshot_observed_at":"2026-08-08T07:57:40.346666Z","submitted_at":"2025-08-14T13:46:47Z","title":"MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-05T20:18:58.629661Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2508.13186"},"observation_digest":"sha256:9d795bae61f144b1d0129e1c32879c483956f06f023e491eb50cf4c32e52082b","observation_id":"66900148-4dd5-4a78-bd8c-4b461a3f19fc","resolution":{"observed_at":"2026-08-05T20:18:58.629661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2509.07969","last_updated":"2025-09-09T17:54:21Z","snapshot_observed_at":"2026-07-30T05:21:39.737665Z","submitted_at":"2025-09-09T17:54:21Z","title":"Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-18T01:17:55.500268Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2509.07969"},"observation_digest":"sha256:4000c693e2f27d3fba8a89ca30b98aa41238e70a6a4ea20a49cbcec93375c9fe","observation_id":"e3eace9c-2aa3-48a9-a23e-147b65808920","resolution":{"observed_at":"2026-05-18T01:17:55.583663Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-04T10:40:42.435539Z","title":"Mmsearch- r1: Incentivizing lmms to search.CoRR, abs/2506.20670,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.09733","last_updated":"2026-07-28T12:35:46Z","snapshot_observed_at":"2026-08-08T01:13:54.575859Z","submitted_at":"2025-10-10T13:34:23Z","title":"VisRAG2.0: Mitigating Visual Hallucinations via Evidence-Guided Multi-Image Reasoning in Visual Retrieval-Augmented Generation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T10:40:42.435539Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2510.09733"},"observation_digest":"sha256:1b22e04534f9061e08421b7da56e240ed84f7f7f3295088fe6b0d41818b50d2f","observation_id":"cd68caac-9f0d-4ae3-90d8-da8961af88f8","resolution":{"observed_at":"2026-08-04T10:40:42.435539Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2511.05271","last_updated":"2026-03-11T08:46:41Z","snapshot_observed_at":"2026-07-06T22:35:13.699594Z","submitted_at":"2025-11-07T14:31:20Z","title":"DeepEyesV2: Toward Agentic Multimodal Model","version":4},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-16T05:32:29.266583Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2511.05271"},"observation_digest":"sha256:798ba502c33aaf3d769332dbb54dd09d0c1e57b6cdaa5c73cbd473524b3e1e64","observation_id":"4b1c2a2a-59ac-4f80-a8f1-8554758f98d7","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2602.22683","last_updated":"2026-04-09T08:16:21Z","snapshot_observed_at":"2026-07-06T22:47:06.893212Z","submitted_at":"2026-02-26T06:55:48Z","title":"SUPERGLASSES: Benchmarking Vision Language Models as Intelligent Agents for AI Smart Glasses","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-15T19:18:36.314029Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2602.22683"},"observation_digest":"sha256:5a2e71d908aeb8b270648a3056af1563c3c22bcd9dd0408c9bf82230cdd54b6e","observation_id":"a1eacd08-7a31-4abc-8e4d-3ebdbbf1c869","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-02T20:40:32.339980Z","title":"Mmsearch-r1: Incentivizing lmms to search","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.22766","last_updated":"2026-06-07T11:29:15Z","snapshot_observed_at":"2026-08-06T01:15:52.220969Z","submitted_at":"2026-02-26T08:56:23Z","title":"Imagination Helps Visual Reasoning, But Not Yet in Latent Space","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T20:40:32.339980Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2602.22766"},"observation_digest":"sha256:380e812de858131b6f0802d3419f7f84bac9226f5730b72ee2f62935957dd72f","observation_id":"7bff5ccd-1286-4353-a6c1-ec7496ccef65","resolution":{"observed_at":"2026-08-02T20:40:32.339980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-15T14:43:21.866055Z","title":"Mmsearch- r1: Incentivizing lmms to search.ArXiv, abs/2506.20670,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.05256","last_updated":"2026-07-02T16:41:10Z","snapshot_observed_at":"2026-08-06T04:07:42.199986Z","submitted_at":"2026-03-05T15:08:06Z","title":"Wiki-R1: Incentivizing Multimodal Reasoning for Knowledge-based VQA via Data and Sampling Curriculum","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-15T14:43:21.866055Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2603.05256"},"observation_digest":"sha256:484b2c94a061ba21f28d47c512983d587f20c55ef95cffbd148ddedbef3f7710","observation_id":"09c7f8a3-dc2b-4c08-8da0-8a6d1fae7926","resolution":{"observed_at":"2026-07-15T14:43:21.866055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.04500","last_updated":"2026-04-06T07:51:59Z","snapshot_observed_at":"2026-07-30T06:32:02.248567Z","submitted_at":"2026-04-06T07:51:59Z","title":"Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-10T19:59:19.379119Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.04500"},"observation_digest":"sha256:8cd169a110e50bb3b4f0d151d2bc6b6613f84dfec7a4e5605164529837484b52","observation_id":"fbc28abd-268c-46d8-9b11-342a292ef159","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.06777","last_updated":"2026-04-08T07:48:07Z","snapshot_observed_at":"2026-08-06T14:41:06.876472Z","submitted_at":"2026-04-08T07:48:07Z","title":"Walk the Talk: Bridging the Reasoning-Action Gap for Thinking with Images via Multimodal Agentic Policy Optimization","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-10T18:20:02.559108Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.06777"},"observation_digest":"sha256:4410520ca0fc3c9f0960549b214116312a95dbde67f496d226c2f1a734c4ec05","observation_id":"98f7b2a9-196c-4e0a-bc8e-28aa5b145015","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.08545","last_updated":"2026-04-09T17:59:57Z","snapshot_observed_at":"2026-08-10T23:18:23.568914Z","submitted_at":"2026-04-09T17:59:57Z","title":"Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T18:35:21.514502Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.08545"},"observation_digest":"sha256:66c0f593597ac47869d2baf6c366f40deaf3cf1ee4d22496725d43a220b37072","observation_id":"a5d6983e-eb40-4cf4-a06b-42201088f958","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.09508","last_updated":"2026-04-10T17:25:34Z","snapshot_observed_at":"2026-07-06T22:58:21.624968Z","submitted_at":"2026-04-10T17:25:34Z","title":"VISOR: Agentic Visual Retrieval-Augmented Generation via Iterative Search and Over-horizon Reasoning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T17:45:21.088097Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.09508"},"observation_digest":"sha256:55fa43ee8fb18e7949f727450590a64ab0a3c8d89f9525498501116885e0fde7","observation_id":"32d2fd6d-559e-47cc-8446-a87dbe1f013a","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.12890","last_updated":"2026-04-25T02:32:57Z","snapshot_observed_at":"2026-08-11T09:04:45.578410Z","submitted_at":"2026-04-14T15:40:28Z","title":"Towards Long-horizon Agentic Multimodal Search","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-10T15:40:32.137708Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.12890"},"observation_digest":"sha256:abfe6408477cde06ad873f4fea55f1653a3f0866fcdfa2259fd6bc8a465aca33","observation_id":"a1052331-2a0f-445b-85f2-b9ef4fc22d1c","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.14029","last_updated":"2026-07-29T13:04:29Z","snapshot_observed_at":"2026-08-11T10:37:46.934045Z","submitted_at":"2026-04-15T16:09:37Z","title":"POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-10T13:09:24.304696Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.14029"},"observation_digest":"sha256:111e4fa9b8770f4048ecaaa3ad1f64c1ba3f8383ec3612f87c63579390744d96","observation_id":"c00cc5ef-32c4-4372-9745-48b715a6ca9f","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-02T16:18:24.971075Z","title":"arXiv preprint arXiv:2506.20670 (2025) 1, 2, 4, 6, 9, 11","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.14029","last_updated":"2026-07-29T13:04:29Z","snapshot_observed_at":"2026-08-11T10:37:46.934045Z","submitted_at":"2026-04-15T16:09:37Z","title":"POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-02T16:18:24.971075Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.14029"},"observation_digest":"sha256:3f695e0399c33a48cc120f2bcbb070cc005713cd13f83ca5dfae847adeffcc33","observation_id":"ef60458e-b334-4276-b91a-29788589cf9c","resolution":{"observed_at":"2026-08-02T16:18:24.971075Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.19264","last_updated":"2026-04-21T09:28:34Z","snapshot_observed_at":"2026-07-31T12:03:21.545054Z","submitted_at":"2026-04-21T09:28:34Z","title":"DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-10T03:21:30.732925Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.19264"},"observation_digest":"sha256:f53b6df86f9b6a06a9f801517cd5cfc5ec53d50981658d0525e73b49a21814bb","observation_id":"21d91918-c6f8-4d17-ba01-a061e7dafa04","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.20146","last_updated":"2026-04-22T03:17:36Z","snapshot_observed_at":"2026-07-31T11:13:50.805703Z","submitted_at":"2026-04-22T03:17:36Z","title":"SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-09T23:55:38.464653Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.20146"},"observation_digest":"sha256:1b8581340418ceee9642b4c23e8c48768306cb5e6386a301cc511798d6d863e3","observation_id":"cd522317-4f8d-45a3-8b10-03728ead3ea1","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2604.20486","last_updated":"2026-04-22T12:20:46Z","snapshot_observed_at":"2026-08-11T01:47:12.769599Z","submitted_at":"2026-04-22T12:20:46Z","title":"ProMMSearchAgent: A Generalizable Multimodal Search Agent Trained with Process-Oriented Rewards","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T01:12:17.469552Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2604.20486"},"observation_digest":"sha256:8c43e0a1a2a0cc03d6316263b11c899cd95fd1fac2a045eee682144edd466065","observation_id":"ae4604a3-1f7b-40d0-bf42-6af2794a5f26","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.02378","last_updated":"2026-05-04T09:18:19Z","snapshot_observed_at":"2026-07-06T23:15:27.816549Z","submitted_at":"2026-05-04T09:18:19Z","title":"Enhancing Multimodal In-Context Learning via Inductive-Deductive Reasoning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T19:21:30.235583Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.02378"},"observation_digest":"sha256:70ae6e9bc9b6cd0c7d2f4bad3dbf914c710bf6e7ffc25799facfab06f9209ab3","observation_id":"a69b98a7-d6f5-4ab4-96e5-c2d293e0f667","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.07177","last_updated":"2026-05-11T11:21:13Z","snapshot_observed_at":"2026-08-03T10:59:43.380213Z","submitted_at":"2026-05-08T03:16:08Z","title":"HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-11T01:28:36.266167Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.07177"},"observation_digest":"sha256:cba46bb868e134328cad7ec1c0cebd24727d4c310b6fa26fbf92c381e06120f0","observation_id":"97dbcb58-cdb0-4f38-b724-bca8ef5f4491","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.07177","last_updated":"2026-05-11T11:21:13Z","snapshot_observed_at":"2026-08-03T10:59:43.380213Z","submitted_at":"2026-05-08T03:16:08Z","title":"HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-12T03:18:01.006274Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.07177"},"observation_digest":"sha256:8f8cac68af5b0c31ea4e8064780337114c2e3708f09de0fd24943e8c6bdb4a43","observation_id":"3d58b791-aad1-4b99-85ac-0c54399895b7","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.09271","last_updated":"2026-05-10T02:42:29Z","snapshot_observed_at":"2026-08-10T21:45:52.315357Z","submitted_at":"2026-05-10T02:42:29Z","title":"Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding","version":1},"reference_index":115,"source":"pdf_text","source_observed_at":"2026-05-12T05:01:38.118237Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.09271"},"observation_digest":"sha256:eb9c541607dbe6189277c112a5a31dab3685bd27a30e9d2ad2e32be95422af70","observation_id":"ea0027b8-c6c1-48e5-8029-b661a0d3b388","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.09934","last_updated":"2026-05-11T03:32:55Z","snapshot_observed_at":"2026-08-11T05:22:49.605607Z","submitted_at":"2026-05-11T03:32:55Z","title":"TRACER: Verifiable Generative Provenance for Multimodal Tool-Using Agents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-12T04:30:06.869916Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.09934"},"observation_digest":"sha256:a9f3dd754ad24e0a723abfc4967713a35e500df9be875d92f29893376d87a9d6","observation_id":"1fc50911-949d-4034-8a8f-e9b6559d0882","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.10832","last_updated":"2026-06-05T07:49:38Z","snapshot_observed_at":"2026-08-11T08:57:01.291196Z","submitted_at":"2026-05-11T16:49:36Z","title":"Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-12T04:15:40.042348Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.10832"},"observation_digest":"sha256:0cc2219ed4c491c061cc3ff52b4995764d60de3d437b8a0ba739de686c393296","observation_id":"f2493802-9861-4579-9227-db8bc8256bcd","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.10832","last_updated":"2026-06-05T07:49:38Z","snapshot_observed_at":"2026-08-11T08:57:01.291196Z","submitted_at":"2026-05-11T16:49:36Z","title":"Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T22:30:28.649803Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.10832"},"observation_digest":"sha256:8c1902781fe24c18492d5054acc67fa762ae0b2d86b2cbd436b5894eed651b6f","observation_id":"9f71c008-bec7-461a-b959-7014430e8afc","resolution":{"observed_at":"2026-07-01T13:55:46.367947Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.12497","last_updated":"2026-05-12T17:59:51Z","snapshot_observed_at":"2026-08-02T08:24:58.437346Z","submitted_at":"2026-05-12T17:59:51Z","title":"From Web to Pixels: Bringing Agentic Search into Visual Perception","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T05:47:43.959052Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.12497"},"observation_digest":"sha256:405d8a412bdf022d364226fd05d942896d3ac06d16c6c5b52930e2cdeb37af09","observation_id":"c58becbc-3b7f-4f27-9654-b2f21a3b589b","resolution":{"observed_at":"2026-05-16T15:27:04.573030Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.17946","last_updated":"2026-05-20T03:33:36Z","snapshot_observed_at":"2026-07-06T23:28:55.079333Z","submitted_at":"2026-05-18T07:03:48Z","title":"SVFSearch: A Multimodal Knowledge-Intensive Benchmark for Short-Video Frame Search in the Gaming Vertical Domain","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-05-20T10:08:56.397296Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.17946"},"observation_digest":"sha256:7774d4e8303151b12b1c109435ef84cd856e287012662dc6f1803f94f5dbc6f4","observation_id":"16ee1003-fa56-4a5c-9638-2ec5c6390ac6","resolution":{"observed_at":"2026-05-20T10:13:11.977524Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.17946","last_updated":"2026-05-20T03:33:36Z","snapshot_observed_at":"2026-07-06T23:28:55.079333Z","submitted_at":"2026-05-18T07:03:48Z","title":"SVFSearch: A Multimodal Knowledge-Intensive Benchmark for Short-Video Frame Search in the Gaming Vertical Domain","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-05-21T08:49:32.503461Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.17946"},"observation_digest":"sha256:5fe79003988979e30e8b54dab465bf3511c0cf525351ef9325cd128ce2fc9657","observation_id":"8da86291-34ad-4f6b-be1a-723ca61d5518","resolution":{"observed_at":"2026-05-21T08:49:53.433855Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.24733","last_updated":"2026-05-23T20:57:19Z","snapshot_observed_at":"2026-08-02T22:40:48.861037Z","submitted_at":"2026-05-23T20:57:19Z","title":"StepGap: A Hybrid NLI-LLM Checker for Step-Level Evidence-Gap Detectionin Multi-Hop Question Answering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T12:57:12.435921Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.24733"},"observation_digest":"sha256:e041673e908258100dca72cf4446344bd36ea56cc4187a866b284bf21a4f4681","observation_id":"8be9944a-c574-4747-8850-db35f39dba21","resolution":{"observed_at":"2026-06-30T13:04:40.506738Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2605.28774","last_updated":"2026-05-27T17:36:39Z","snapshot_observed_at":"2026-07-06T23:38:19.096349Z","submitted_at":"2026-05-27T17:36:39Z","title":"Agent Explorative Policy Optimization for Multimodal Agentic Reasoning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-29T12:22:39.655615Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2605.28774"},"observation_digest":"sha256:e32b7f4bc7cfb0a8b35cd4755c9a6b33cff15dd2442770ed60e4cc1848d669b4","observation_id":"18460c0e-138e-4c36-9c0d-78b44b18d44a","resolution":{"observed_at":"2026-06-29T12:23:24.115378Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2606.05784","last_updated":"2026-06-04T07:15:43Z","snapshot_observed_at":"2026-08-01T23:01:58.625715Z","submitted_at":"2026-06-04T07:15:43Z","title":"TAPO: Tool-Aware Policy Optimization via Credit Transfer for Multimodal Search Agents","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-06-28T02:11:11.638029Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2606.05784"},"observation_digest":"sha256:58243272a29c751f7aaf030c105f6de1ba59e6dc25cd9a0c7d3ca30f1c9d2f1a","observation_id":"b3ec0336-cebe-4876-8895-943354b939ec","resolution":{"observed_at":"2026-07-02T12:16:57.759885Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2606.23881","last_updated":"2026-06-22T19:27:00Z","snapshot_observed_at":"2026-08-03T12:04:36.736234Z","submitted_at":"2026-06-22T19:27:00Z","title":"Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-06-26T08:12:14.829556Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2606.23881"},"observation_digest":"sha256:2a234eee818e8ebbeb0d5632656c64d4da3683988cd694b1ed9ee904885edc10","observation_id":"a46b1d44-f719-41ce-b224-e9f3468ba641","resolution":{"observed_at":"2026-07-04T10:59:46.852810Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2606.26122","last_updated":"2026-05-27T21:21:42Z","snapshot_observed_at":"2026-08-11T03:18:55.947711Z","submitted_at":"2026-05-27T21:21:42Z","title":"DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-06-29T12:50:16.625077Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2606.26122"},"observation_digest":"sha256:887f4216f1f35be4ed34ee1437ec061ff5203c2de6a0fa6b0f31164bf6ff56c7","observation_id":"062df9cc-7d8c-4e07-9360-b3b013de5ecd","resolution":{"observed_at":"2026-06-29T12:53:26.570865Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2606.27974","last_updated":"2026-06-26T11:23:18Z","snapshot_observed_at":"2026-08-07T04:13:31.113853Z","submitted_at":"2026-06-26T11:23:18Z","title":"ProMSA:Progressive Multimodal Search Agents for Knowledge-Based Visual Question Answering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-29T05:00:50.924136Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2606.27974"},"observation_digest":"sha256:b6e34d49d054a4aa97e7b002a948dcc7e3c0ba7f1c4da3460f92c1794687bbb2","observation_id":"766aa02c-214c-4f64-9a17-f8e4abb8c9a9","resolution":{"observed_at":"2026-06-29T18:53:51.961092Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2606.31504","last_updated":"2026-06-30T11:22:24Z","snapshot_observed_at":"2026-08-08T20:17:46.874902Z","submitted_at":"2026-06-30T11:22:24Z","title":"SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-07-01T06:02:48.532478Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2606.31504"},"observation_digest":"sha256:a1c1391ca98d3b82276d1c9afa285672907989019cb1386df0461d98337cb2ca","observation_id":"49c68206-be00-49d2-98a3-9263f0ea2ccb","resolution":{"observed_at":"2026-07-01T09:55:41.078480Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-12T06:04:16.637378Z","title":"Mmsearch-r1: Incentivizing lmms to search.arXiv preprint arXiv:2506.20670, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02927","last_updated":"2026-07-03T03:50:09Z","snapshot_observed_at":"2026-08-07T23:48:33.179767Z","submitted_at":"2026-07-03T03:50:09Z","title":"VideoSearcher: Empowering Video Deep Research with Multi-Tool Agentic Reasoning via Reinforcement Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-12T06:04:16.637378Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.02927"},"observation_digest":"sha256:1bb764bde76fd346b6df55f115a4aea4963fb7d4a09b3aa1ef19d10dd1809dd7","observation_id":"3e6cf177-c0c2-41f9-8207-04c11ed9b167","resolution":{"observed_at":"2026-07-12T06:04:16.637378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-11T15:24:53.016199Z","title":"MMSearch-R1: Incentivizing LMMs to search.arXiv preprint arXiv:2506.20670, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.05465","last_updated":"2026-07-06T04:57:18Z","snapshot_observed_at":"2026-08-08T10:20:15.118625Z","submitted_at":"2026-07-06T04:57:18Z","title":"CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-11T15:24:53.016199Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.05465"},"observation_digest":"sha256:f2455f2417db3b96ea0a8209b2612971a57fe4f643969562fd5d80cec5492218","observation_id":"db4963ce-c8f2-413d-a49f-f38173e4dbf4","resolution":{"observed_at":"2026-07-11T15:24:53.016199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":"2506.20670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-10T07:26:54.458175Z","title":"MMSearch-R1: Incentivizing LMMs to Search","venue":"cs.CV","work_id":"19069633-beb6-4e5b-a373-e4becafff7eb","year":2025},"citing_paper":{"arxiv_id":"2607.08448","last_updated":"2026-07-15T16:40:12Z","snapshot_observed_at":"2026-08-04T18:37:38.875340Z","submitted_at":"2026-07-09T13:08:54Z","title":"Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-10T07:18:57.823444Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.08448"},"observation_digest":"sha256:9f40f6c88456b8d1678f04dcc117498704cc79bc4ad7b7f557feb2b9387e0fcf","observation_id":"ef44b7d8-c45a-4ff3-8a0b-77c4661c1904","resolution":{"observed_at":"2026-07-10T07:26:54.459431Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-02T07:56:56.595588Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.08448","last_updated":"2026-07-15T16:40:12Z","snapshot_observed_at":"2026-08-04T18:37:38.875340Z","submitted_at":"2026-07-09T13:08:54Z","title":"Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-02T07:56:56.595588Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.08448"},"observation_digest":"sha256:4b6eefe7db76e466bafcf8273af52d112d0a0058c69b693824be93d27ec47b02","observation_id":"0cca97aa-121a-467a-933c-d93da70d0754","resolution":{"observed_at":"2026-08-02T07:56:56.595588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-14T10:51:16.019022Z","title":"arXiv preprint arXiv:2506.20670 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10557","last_updated":"2026-07-12T04:13:27Z","snapshot_observed_at":"2026-08-07T19:26:40.944900Z","submitted_at":"2026-07-12T04:13:27Z","title":"UNIBROWSE: A Data-to-Agent Framework for Multimodal BrowseComp","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-07-14T10:51:16.019022Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.10557"},"observation_digest":"sha256:01192ad0b161c40b8a4f484834a4fb226e2febb7eb39b1470cee091a8a7b174f","observation_id":"8f738df4-6696-4592-8c6d-2d034cfba0d2","resolution":{"observed_at":"2026-07-14T10:51:16.019022Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-01T11:45:55.032110Z","title":"arXiv preprint arXiv:2506.20670 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19793","last_updated":"2026-07-22T06:19:06Z","snapshot_observed_at":"2026-08-09T17:13:03.729227Z","submitted_at":"2026-07-22T06:19:06Z","title":"Silent Failures in Multimodal Agentic Search:A Diagnostic Taxonomy and Cross-Judge Evaluation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T11:45:55.032110Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.19793"},"observation_digest":"sha256:96065be8d34ae4046eb11f1669ad7c519f6d76ced68d157f0a2a89bfadb999a5","observation_id":"0b65e372-1a50-4ec7-bb28-610ca38a9dd9","resolution":{"observed_at":"2026-08-01T11:45:55.032110Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-02T10:20:51.281748Z","title":"arXiv preprint arXiv:2506.20670 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22643","last_updated":"2026-06-24T02:40:49Z","snapshot_observed_at":"2026-08-08T03:20:50.943223Z","submitted_at":"2026-06-24T02:40:49Z","title":"Reason Before You Retrieve: Agentic Planning for Multi-modal RAG","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-02T10:20:51.281748Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.22643"},"observation_digest":"sha256:fbc6210e1aabfda75d4eea1ab5c5ed6b74151de83b4ab64d1a71895d4c06a407","observation_id":"8179bfcf-91ee-4982-abc8-764905b7bf40","resolution":{"observed_at":"2026-08-02T10:20:51.281748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-01T01:14:37.987891Z","title":"arXiv:2506.20670","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27798","last_updated":"2026-07-30T07:36:53Z","snapshot_observed_at":"2026-08-07T23:12:16.555388Z","submitted_at":"2026-07-30T07:36:53Z","title":"MemeBench: What LVLMs Miss When Interpreting Culture-Dependent Memes","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T01:14:37.987891Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.27798"},"observation_digest":"sha256:049110be7edab71bde05c4f01bc21f6d541cdbe46a187fc61d200a97822f4cf4","observation_id":"7184788c-89a2-49b9-81f2-1c297ce91acd","resolution":{"observed_at":"2026-08-01T01:14:37.987891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-07-31T19:16:59.859725Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28055","last_updated":"2026-07-30T11:34:55Z","snapshot_observed_at":"2026-08-05T20:01:13.896714Z","submitted_at":"2026-07-30T11:34:55Z","title":"VIG-RL: Learning to Search and Insert for Verified Image Grounding","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-07-31T19:16:59.859725Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2607.28055"},"observation_digest":"sha256:91af5fd9bce41a05aeecc14e2ce32b5d16123ee18380acb358bfc19a0e3d4f39","observation_id":"5baf118b-e99b-4f23-9cf4-4312e2ea67a0","resolution":{"observed_at":"2026-07-31T19:16:59.859725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-04T20:12:42.088950Z","title":"Huanjin Yao, Qixiang Yin, Min Yang, Ziwang Zhao, Yibo Wang, Haotian Luo, Jingyi Zhang, and Jiaxing Huang","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.01827","last_updated":"2026-08-03T07:36:48Z","snapshot_observed_at":"2026-08-09T01:05:04.453435Z","submitted_at":"2026-08-03T07:36:48Z","title":"DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T20:12:42.088950Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2608.01827"},"observation_digest":"sha256:b54b73b2d0b13bb13d362f3e04ffa2125fc3398466b0e2609b038a7b78c1ac17","observation_id":"496c2b04-519a-410b-9bee-1d53c9b93c69","resolution":{"observed_at":"2026-08-04T20:12:42.088950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-05T04:44:28.704735Z","title":"arXiv preprint arXiv:2506.20670 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03979","last_updated":"2026-08-04T17:45:16Z","snapshot_observed_at":"2026-08-10T11:27:22.684781Z","submitted_at":"2026-08-04T17:45:16Z","title":"Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T04:44:28.704735Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2608.03979"},"observation_digest":"sha256:caffea40157cee7f94923e142cf3cf14d81037d9e66abce8918c8c2ae2dd4be3","observation_id":"637e9dc8-9f97-41b9-8b13-f92c671435e6","resolution":{"observed_at":"2026-08-05T04:44:28.704735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20670","snapshot_observed_at":"2026-08-10T22:17:20.613684Z","title":"arXiv preprint arXiv:2506.20670","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06699","last_updated":"2026-08-07T01:52:45Z","snapshot_observed_at":"2026-08-11T10:10:18.981212Z","submitted_at":"2026-08-07T01:52:45Z","title":"AgentPatch: Coarse-to-Fine Weak-Task Repair for Merging Agentic Multimodal Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T22:17:20.613684Z"},"links":{"cited_paper":"/paper/2506.20670","citing_paper":"/paper/2608.06699"},"observation_digest":"sha256:d95a9517c4901317535d6e8b7a369b6c05a9cfb84634a22aaf70179072742f2e","observation_id":"97be0b3f-9e47-4d58-b683-133ab4355bcb","resolution":{"observed_at":"2026-08-10T22:17:20.613684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.20670/citation-record","integrity":"/paper/2506.20670/integrity","json":"/paper/2506.20670/citation-record.json","paper":"/paper/2506.20670"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.20201","last_updated":"2025-03-26T03:51:32Z","snapshot_observed_at":"2026-08-10T18:45:49.324978Z","submitted_at":"2025-03-26T03:51:32Z","title":"Open Deep Search: Democratizing Search with Open-source Reasoning Agents","version":1},"cited_work":{"arxiv_id":"2503.20201","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.20201","snapshot_observed_at":"2026-07-03T05:57:41.492145Z","title":"Open deep search: Democratizing search with open-source reasoning agents","venue":null,"work_id":"467e5b5b-a169-4539-8ddc-bd34e07b0e3a","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2503.20201","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:23e6902f200f6644f4d84ee5aa7f4481c8d588e40754ecb59dbaeccd4fcb1d37","observation_id":"b3f02d48-beee-40de-8368-a35c283bdf17","resolution":{"observed_at":"2026-05-16T15:27:04.453500Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Claude 3.5 Sonnet","venue":null,"work_id":"45d58c07-b237-4bb8-ac8d-8c68f4784507","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:2d377aacd5f1ba8ec2e86342c9e95c40575955dc69adecc9d8a94998b7cfbc33","observation_id":"2b362c8d-c99e-4f37-a75b-78b41b63d8cc","resolution":{"observed_at":"2026-05-16T15:27:04.478349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Self-rag: Learn- ing to retrieve, generate, and critique through self-reflection","venue":null,"work_id":"cd9884d5-53dc-4ba6-98d6-a38b02cf052e","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:931a343ea847af0023baa719bd19d6bbb372d23682495bd75dd291d49e314575","observation_id":"625d3721-6cde-4d01-bafb-c962a895ca27","resolution":{"observed_at":"2026-05-16T15:27:04.480784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mint-1t: Scaling open-source multimodal data by 10x: A multimodal dataset with one trillion tokens","venue":null,"work_id":"9350a215-8bdd-4a04-a217-295413298f83","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:26d58844c1b166d8f73136a22d040d908fa4f552706ac013c65cde62306516b8","observation_id":"84906075-6742-4281-96ee-7d57e6435752","resolution":{"observed_at":"2026-05-16T15:27:04.482790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":"2502.13923","doi":"10.48550/arxiv.2502.13923","metadata_source":"pith","pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen2.5-VL Technical Report","venue":"cs.CV","work_id":"69dffacb-bfe8-442d-be86-48624c60426f","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6a061e727dc60ad44e5ccf2d4cf043cd115e958a038feff429d092f71d297d13","observation_id":"ab1be163-2f60-4fd9-8ba7-0c5d9858f06b","resolution":{"observed_at":"2026-05-16T15:27:04.319900Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-08T16:08:16.864468+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-08T16:08:16.864468+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"How do large language models acquire factual knowledge during pretraining? In The Thirty-eighth Annual Conference on Neural Information Processing Systems","venue":null,"work_id":"e2a29b98-8a9e-4192-aa2a-2452424d8381","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:73e8af27894330e7231e7adc05a80bc78ccd1b0091e0cdb3b3364bfc1d942658","observation_id":"81c8a7bf-6a14-4346-bedc-8854aa638b90","resolution":{"observed_at":"2026-05-16T15:27:04.485050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.19470","last_updated":"2025-09-23T03:45:42Z","snapshot_observed_at":"2026-08-10T03:47:52.773511Z","submitted_at":"2025-03-25T09:00:58Z","title":"ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning","version":3},"cited_work":{"arxiv_id":"2503.19470","doi":"10.48550/arxiv.2503.19470","metadata_source":"pith","pith_arxiv_id":"2503.19470","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning","venue":"cs.AI","work_id":"cc9775d9-2fbd-4690-a641-2b50ae4a59dc","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2503.19470","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:f9546ac87e3f75fd3fb6bd9e58406865f5e4599ebf1611429bed1ae0ff950787","observation_id":"e6f0ccc0-697e-4151-bf65-fca28838351b","resolution":{"observed_at":"2026-05-16T15:48:34.842623Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02928","last_updated":"2022-10-20T17:16:27Z","snapshot_observed_at":"2026-08-06T23:46:49.824788Z","submitted_at":"2022-10-06T13:58:03Z","title":"MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text","version":2},"cited_work":{"arxiv_id":"2210.02928","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.02928","snapshot_observed_at":"2026-07-03T13:48:20.245870Z","title":"Murag: Multimodal retrieval-augmented generator for open question answering over images and text","venue":null,"work_id":"f9b8c687-c024-4fa7-99c3-c12c240ca6f9","year":2022},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2210.02928","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:a45b691a990873c882d48bd5a4014544c56a29cc1cd6a82b5d55ff6f4fafa975","observation_id":"afc29005-0b74-436e-829b-b6689c930461","resolution":{"observed_at":"2026-05-16T15:27:04.416827Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.11713","last_updated":"2023-10-17T14:19:13Z","snapshot_observed_at":"2026-08-10T06:24:49.807173Z","submitted_at":"2023-02-23T00:33:54Z","title":"Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?","version":5},"cited_work":{"arxiv_id":"2302.11713","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2302.11713","snapshot_observed_at":"2026-07-04T10:59:46.832017Z","title":"Can pre-trained vision and language models answer visual information-seeking questions?","venue":null,"work_id":"b7899c66-9ee1-45bf-8a1d-223b8959dee6","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2302.11713","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:3cffa5359ee77caef7cd79db0e1673175fe9602f76cf5d093a6f557d46d4bf07","observation_id":"17b0c8a1-b73e-4bf0-bf58-3901c577b7e7","resolution":{"observed_at":"2026-05-16T15:27:04.427821Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21439","last_updated":"2024-09-25T06:14:03Z","snapshot_observed_at":"2026-07-06T18:54:54.118506Z","submitted_at":"2024-07-31T08:43:17Z","title":"MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training","version":2},"cited_work":{"arxiv_id":"2407.21439","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.21439","snapshot_observed_at":"2026-07-02T03:26:29.522095Z","title":"Mllm is a strong reranker: Advancing multimodal retrieval-augmented generation via knowledge-enhanced reranking and noise-injected training","venue":null,"work_id":"d9e9bf89-3747-4dd8-8467-3a799ed1809e","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2407.21439","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:e4615ea7fc3a3ee6cf3cf2624647c518c337b32af75f85ae132943be2b8fcbbd","observation_id":"0eb58194-925d-49d8-983b-041ace8443a5","resolution":{"observed_at":"2026-05-16T15:27:04.434875Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks","venue":null,"work_id":"8db91de3-4a01-4005-b137-61e455de11dd","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:d81751556e231363820f6875da1922420590c49a9235575333505e4fab112d2c","observation_id":"e17188d3-2f44-40b3-8900-0edc37622f60","resolution":{"observed_at":"2026-05-16T15:27:04.488440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08518","last_updated":"2023-12-16T06:50:09Z","snapshot_observed_at":"2026-08-10T12:59:38.575250Z","submitted_at":"2023-03-15T10:53:49Z","title":"UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation","version":4},"cited_work":{"arxiv_id":"2303.08518","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.08518","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Uprise: Universal prompt retrieval for improving zero-shot evaluation","venue":null,"work_id":"d19f7028-ce03-4dcc-a4f3-6c335d6afc84","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2303.08518","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:566fd92daffe981ee00397a8ea94d82f09ebfea2b9aabac7130ef81f3ac8dd8a","observation_id":"fbc4531d-c318-4367-899c-a4fa4613917c","resolution":{"observed_at":"2026-05-16T15:27:04.337424Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13059","last_updated":"2025-02-18T17:04:26Z","snapshot_observed_at":"2026-08-08T21:47:37.522002Z","submitted_at":"2025-02-18T17:04:26Z","title":"SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models","version":1},"cited_work":{"arxiv_id":"2502.13059","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.13059","snapshot_observed_at":"2026-07-03T04:27:37.001216Z","title":"SimpleVQA: Multimodal factuality evaluation for multimodal large lan- guage models.arXiv preprint arXiv:2502.13059","venue":null,"work_id":"7361c370-5f61-4dc9-b6dc-07820cd870cf","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2502.13059","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:545ab31f6befea8a3abf1dc3d21a5c7bf2d43c53784195d4b98523880e8b44ad","observation_id":"c27950f7-ce82-4e43-ae90-7b358097072c","resolution":{"observed_at":"2026-05-16T15:27:04.346211Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Claude takes research to new places","venue":null,"work_id":"a788a22a-73c6-4b19-b370-96584c246771","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:02ca02bacc9efeebc0f34cec4374accd799781fa09adfd9ba6eb53e612e6e69e","observation_id":"8dbab8bf-71f3-41b5-8021-4cfc77f8f8bc","resolution":{"observed_at":"2026-05-16T15:27:04.490611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.03287","last_updated":"2023-11-07T02:18:48Z","snapshot_observed_at":"2026-08-10T17:39:51.703002Z","submitted_at":"2023-11-06T17:26:59Z","title":"Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges","version":2},"cited_work":{"arxiv_id":"2311.03287","doi":"10.48550/arxiv.2311.03287","metadata_source":"arxiv_reference","pith_arxiv_id":"2311.03287","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Holistic analysis of hallucination in gpt-4v (ision): Bias and interference chal- lenges","venue":"arXiv (Cornell University)","work_id":"a39b177c-6624-4310-9837-526645915677","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2311.03287","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:a98e5fdc4d206ffb3d6c3235cd251c2288ce47edd91b1940f97e816d0155b6b8","observation_id":"7dc3ed3a-6c1c-4447-86d3-7920bfa1d718","resolution":{"observed_at":"2026-05-16T15:27:04.393958Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05952","last_updated":"2025-06-09T02:56:55Z","snapshot_observed_at":"2026-08-10T21:03:53.066779Z","submitted_at":"2025-01-10T13:27:04Z","title":"Scalable Vision Language Model Training via High Quality Data Curation","version":3},"cited_work":{"arxiv_id":"2501.05952","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05952","snapshot_observed_at":"2026-07-04T15:09:55.276573Z","title":"Scalable vision language model training via high quality data curation","venue":null,"work_id":"454a0bb0-39e7-41e0-9791-e92ea63dfd82","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2501.05952","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b2d7eb11bd6159951a3090b993b8e37d0ebc323ddd095a6300d78d0cf36f2c17","observation_id":"e768521e-f731-4390-ba9b-14a09ac76714","resolution":{"observed_at":"2026-05-16T15:27:04.398232Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13394","last_updated":"2025-10-24T02:45:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-23T09:22:36Z","title":"MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models","version":5},"cited_work":{"arxiv_id":"2306.13394","doi":"10.48550/arxiv.2306.13394","metadata_source":"pith","pith_arxiv_id":"2306.13394","snapshot_observed_at":"2026-07-10T13:27:05.561984Z","title":"MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models","venue":"cs.CV","work_id":"806d2e73-71b3-4d56-87e0-39d571cc15d6","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2306.13394","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:5e7dd459c0f5789597955d0362aa482eea032fb73b52a0d7349b3b5813426d4d","observation_id":"8c6549d0-0175-448d-87be-5f40f198498d","resolution":{"observed_at":"2026-05-16T15:27:04.405020Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-08T16:08:17.033703+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-08T16:08:17.033703+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.05288","last_updated":"2025-07-01T02:17:31Z","snapshot_observed_at":"2026-08-10T13:24:26.889977Z","submitted_at":"2025-04-07T17:39:31Z","title":"Seeking and Updating with Live Visual Knowledge","version":2},"cited_work":{"arxiv_id":"2504.05288","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.05288","snapshot_observed_at":"2026-07-04T10:59:46.865978Z","title":"Livevqa: Live visual knowledge seeking","venue":null,"work_id":"9c3a30df-d4d6-4c09-bef9-7b59689aa66c","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2504.05288","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:9053f7190d0264cde2ea48fc8064c3b36cfcd21d345708814424c9ed6f6df6d6","observation_id":"fc9fc268-79b7-4c0d-8317-fa1eeb9a0aa9","resolution":{"observed_at":"2026-05-16T15:27:04.408857Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Try Deep Research and our new experimental model in Gemini, your AI assistant","venue":null,"work_id":"f8c67b64-ae71-4c6b-8738-5eaf8ce88ea0","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:4b67b5a4090da8badc1fbb1ef660c3334107d32a0c386cf4b79786b9f619fd9c","observation_id":"4f2ea191-b141-4293-b095-e984551c2564","resolution":{"observed_at":"2026-05-16T15:27:04.492762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2501.12948","doi":"10.1016/j.artmed.2024.103001","metadata_source":"pith","pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","venue":"cs.CL","work_id":"e6b75ad5-2877-4168-97c8-710407094d20","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:7bb9bc14e7ccfe276bd9577466fae5c22774f1cc38a1df1c8bb7728fc3b1a775","observation_id":"33cb84f8-64e7-4a44-b8f2-adc2ce9e73a8","resolution":{"observed_at":"2026-05-16T15:27:04.420764Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Avis: Autonomous visual information seeking with large language model agent","venue":null,"work_id":"12a83cb4-1796-4fc3-8c33-6a53db7edbba","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:d2ca7b8610cc0c2f3a724560b780e6183a69dd0092656ff0cd939c2f69e3b666","observation_id":"aef7d841-ab9a-4945-8825-db8c755cbb90","resolution":{"observed_at":"2026-05-16T15:27:04.494964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reveal: Retrieval-augmented visual-language pre-training with multi-source multimodal knowledge memory","venue":null,"work_id":"175747e1-edcd-4413-be8d-eab4029be6c7","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:7ab9945d5c403fc8b7564114cc0665a8ea62918c45df27ea47a58b6fadcd2e8f","observation_id":"92624386-99e4-4d74-996c-847ef51f12a4","resolution":{"observed_at":"2026-05-16T15:27:04.497149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":"2410.21276","doi":"10.1177/15248380231178756","metadata_source":"pith","pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4o System Card","venue":"cs.CL","work_id":"f37bf1c7-4964-4e56-9762-d20da8d9009f","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:72441e47497aa0f3da2c91be50052a5d78704a496927c99d2e813580f2723fa8","observation_id":"e7a9fb1a-f6cd-4f9b-bcb6-4a4882016b2b","resolution":{"observed_at":"2026-05-16T15:27:04.437925Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.03299","last_updated":"2022-11-16T16:38:18Z","snapshot_observed_at":"2026-08-05T00:57:17.859949Z","submitted_at":"2022-08-05T17:39:22Z","title":"Atlas: Few-shot Learning with Retrieval Augmented Language Models","version":3},"cited_work":{"arxiv_id":"2208.03299","doi":null,"metadata_source":"pith","pith_arxiv_id":"2208.03299","snapshot_observed_at":"2026-07-03T17:48:46.017911Z","title":"Atlas: Few-shot Learning with Retrieval Augmented Language Models","venue":"cs.CL","work_id":"3bffc484-91bd-41a2-9e31-922d0c311a12","year":2022},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2208.03299","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:042bfa2c9e6b30e04fbfb36a52ed64b362b22833e72ecd4423bbb22f41f42034","observation_id":"28eded4e-e308-4e13-b49f-a6b320117d0e","resolution":{"observed_at":"2026-05-16T15:27:04.441724Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:2fdd2c1e2254deb521c7fba685ed5989645c5824c10d47f8bfecd6a9dd2186f3","observation_id":"253b989b-4dec-4533-bc0c-94017bd55637","resolution":{"observed_at":"2026-05-16T15:27:04.445309Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12959","last_updated":"2024-11-27T08:49:12Z","snapshot_observed_at":"2026-08-10T08:10:46.203990Z","submitted_at":"2024-09-19T17:59:45Z","title":"MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines","version":2},"cited_work":{"arxiv_id":"2409.12959","doi":"10.48550/arxiv.2409.12959","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.12959","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Bowen Jin, Hansi Zeng, Zhenrui Yue, Jinsung Yoon, Sercan Arik, Dong Wang, Hamed Zamani, and Jiawei Han","venue":"arXiv (Cornell University)","work_id":"d0ff946f-7130-4450-bc8f-42251af6e2c8","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2409.12959","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:e8f38dfbdc78a78e578cffd316300acb5a6bf90f00ef89d7757b450d5acbeda0","observation_id":"36326ec6-1812-41b4-b231-95a60536033c","resolution":{"observed_at":"2026-05-16T15:27:04.449101Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09516","last_updated":"2025-08-05T19:08:38Z","snapshot_observed_at":"2026-07-06T20:51:28.022519Z","submitted_at":"2025-03-12T16:26:39Z","title":"Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning","version":5},"cited_work":{"arxiv_id":"2503.09516","doi":"10.48550/arxiv.2503.09516","metadata_source":"pith","pith_arxiv_id":"2503.09516","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning","venue":"cs.CL","work_id":"0e0b7549-2bc4-4574-aa7f-588ffa16eaae","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2503.09516","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:ce2440ec9c1fec00ddede0e30030e6663e99708c285804297ac65c0af5bc699e","observation_id":"416f2c83-98f1-45d1-ab3a-ffc11c2fa6c0","resolution":{"observed_at":"2026-05-16T15:27:04.278615Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models struggle to learn long-tail knowledge","venue":null,"work_id":"23808563-ad55-4ec3-baad-42c2d9c24659","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6f64aeee10a5da4decb9cfbbb346c4888b55db87ced337b9302deb7ea9f3838a","observation_id":"198d83fa-4cb1-41f8-a63a-b6c6df0c9ccb","resolution":{"observed_at":"2026-05-16T15:27:04.499358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dense passage retrieval for open-domain question answering","venue":null,"work_id":"1a9d8426-3a0a-4ae0-9568-b198c08a63a9","year":2020},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6f0551882b5488f516b145c76a5761fcf1ea95272a1eddc631a0b12b5bc78659","observation_id":"9753edec-3a83-4dc8-a8aa-4ad693358f43","resolution":{"observed_at":"2026-05-16T15:27:04.501756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A diagram is worth a dozen images","venue":null,"work_id":"aded89e6-0b7e-4be0-898a-0655701a66c8","year":2016},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:e91dd73a5eabaada3129225b88cd5ec415246c720270875e13bfa455ff8f1f59","observation_id":"18482141-03af-44a0-b45f-6583cf29fd4d","resolution":{"observed_at":"2026-05-16T15:27:04.503895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","venue":null,"work_id":"be13364b-40b7-43b9-a134-06169e84fce5","year":2020},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:cb7d7b87696d68fd4cbffd76431047772b6421e9d01b05fb2b576a5a4cfcbaca","observation_id":"c2233a85-117c-4f2a-98f8-064393a32ed1","resolution":{"observed_at":"2026-05-16T15:27:04.506750Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03326","last_updated":"2024-10-26T16:35:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:59:44Z","title":"LLaVA-OneVision: Easy Visual Task Transfer","version":3},"cited_work":{"arxiv_id":"2408.03326","doi":"10.48550/arxiv.2408.03326","metadata_source":"pith","pith_arxiv_id":"2408.03326","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LLaVA-OneVision: Easy Visual Task Transfer","venue":"cs.CV","work_id":"f5f2452b-f2a9-49ac-b38d-c76e18cdfe49","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2408.03326","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:60cc2d1cdb15b2f36dbf6ed24c14283e4ee1b56d4282e545e00ae86eee5a9785","observation_id":"f7c2fb4b-b5b0-4b41-9c7a-8a85ec75b0d5","resolution":{"observed_at":"2026-05-16T15:27:04.376631Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05993","last_updated":"2025-01-10T08:35:13Z","snapshot_observed_at":"2026-08-10T13:50:34.044232Z","submitted_at":"2024-10-08T12:44:57Z","title":"Aria: An Open Multimodal Native Mixture-of-Experts Model","version":4},"cited_work":{"arxiv_id":"2410.05993","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.05993","snapshot_observed_at":"2026-07-04T07:49:39.565893Z","title":"Aria: An open multimodal native mixture-of- experts model","venue":null,"work_id":"8ed8984e-244e-4c69-9fd5-c0cef9869673","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2410.05993","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:c2760f7078e8bb88aef52de184a7ea8c14c84fe6f00c647568240cce850c9377","observation_id":"e9d3eefd-96c8-4e8b-ad0a-a00b44db0101","resolution":{"observed_at":"2026-05-16T15:27:04.381238Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10355","last_updated":"2023-10-26T02:52:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T16:34:01Z","title":"Evaluating Object Hallucination in Large Vision-Language Models","version":3},"cited_work":{"arxiv_id":"2305.10355","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.10355","snapshot_observed_at":"2026-07-10T11:37:03.198858Z","title":"Evaluating Object Hallucination in Large Vision-Language Models","venue":"cs.CV","work_id":"66d8ac3e-c134-4995-b528-550afa17586f","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2305.10355","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:5c6d15797685c8ef1f1947cf31b729927fe0cd5908de67c9263fd469a5a097c0","observation_id":"59c82d87-8915-4ac6-8908-000316365be2","resolution":{"observed_at":"2026-05-16T15:27:04.385470Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.07536","last_updated":"2024-08-24T09:59:31Z","snapshot_observed_at":"2026-08-09T12:57:26.889830Z","submitted_at":"2023-11-13T18:22:32Z","title":"A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2311.07536","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.07536","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A comprehensive evaluation of gpt-4v on knowledge-intensive visual question answering","venue":null,"work_id":"5400c5f8-efe6-48ab-8d37-9f49ddd8a61f","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2311.07536","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:71d6226b58271a67b2e8ed6ae6c5a70dd7690cb2f9b20238dc5f3df140a20daa","observation_id":"76fe4f3e-dc22-4423-82b0-4cb02ef50ad0","resolution":{"observed_at":"2026-05-16T15:27:04.389741Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"LLaV A-NeXT: Stronger LLMs Supercharge Multimodal Capabilities in the Wild","venue":null,"work_id":"d8580147-c7bd-4024-bb32-3928fb46788d","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:9092687da45e81ed7d3f361623d20d446a45fd88bff8abb01cd9b2f7ae9bfd68","observation_id":"afe43553-4973-4945-9a71-66dafbc68c34","resolution":{"observed_at":"2026-05-16T15:27:04.509962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vila: On pre-training for visual language models","venue":null,"work_id":"eeb873c0-6697-4a5d-b53f-26d7db9473d6","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:68575ac50722de1dd2cd2384779336694cda17a5f12f78f73d07f24f366eb1a5","observation_id":"0fffc850-59dd-4d0f-a73c-5c113d6ebe2d","resolution":{"observed_at":"2026-05-16T15:27:04.513545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00253","last_updated":"2024-05-06T01:10:01Z","snapshot_observed_at":"2026-08-11T03:31:28.001151Z","submitted_at":"2024-02-01T00:33:21Z","title":"A Survey on Hallucination in Large Vision-Language Models","version":2},"cited_work":{"arxiv_id":"2402.00253","doi":"10.48550/arxiv.2402.00253","metadata_source":"pith","pith_arxiv_id":"2402.00253","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Survey on Hallucination in Large Vision-Language Models","venue":"cs.CV","work_id":"d92dd1ae-69e1-403f-a254-307f138cf24f","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2402.00253","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:a3ca7315841cfbb0913b278662e5e21a570f041b7b4137ceae9a4a70b2226902","observation_id":"db0e5503-8a13-4c50-ad98-7e8f537ac9b7","resolution":{"observed_at":"2026-05-16T15:27:04.401462Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-05-25T22:53:40.09616+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T22:53:40.09616+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Visual instruction tuning.Advances in neural information processing systems","venue":null,"work_id":"96795ad9-a0f8-4285-8265-c1e1e5fe3d97","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:232b10171f41e03097b6187df8fbd064140257d1840861c6d51f7a1089febc4a","observation_id":"afa913b8-4148-4c06-b76c-4cdcb59e3154","resolution":{"observed_at":"2026-05-16T15:27:04.516944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ocrbench: on the hidden mystery of ocr in large multimodal models","venue":null,"work_id":"a50e67f9-0c06-4ad9-a335-7d36dfd2735c","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:5556a92428b031d2721ad8859b67631a53a3e0ca19cdc23ee86d1c368ff027c6","observation_id":"2f7512d4-8f89-46c8-8708-e03762d56927","resolution":{"observed_at":"2026-05-16T15:27:04.519788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02255","last_updated":"2024-01-21T03:47:06Z","snapshot_observed_at":"2026-07-06T16:27:15.027202Z","submitted_at":"2023-10-03T17:57:24Z","title":"MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts","version":3},"cited_work":{"arxiv_id":"2310.02255","doi":"10.1109/cvpr52734.2025.01245","metadata_source":"pith","pith_arxiv_id":"2310.02255","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts","venue":"cs.CV","work_id":"e22c3789-9e71-4242-b6ea-3e60e06e2b66","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2310.02255","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:57da2131d7a1df9b5f73528d2244b2332661175fcf7c57c8b430ccbe0b3f3931","observation_id":"d9c39839-9e53-4959-ad6d-8aa6b57253b8","resolution":{"observed_at":"2026-05-16T15:27:04.412789Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Search augmented instruction learning","venue":null,"work_id":"e1295e58-62f0-49d3-b85e-9cb99076fa89","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:df67a345fda620523ba538b241e46c519744279c96d6ce2f599af6f4979cc4b5","observation_id":"429a4f91-792e-4609-a8c8-c7c4373c8e1b","resolution":{"observed_at":"2026-05-16T15:27:04.522242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ok-vqa: A visual question answering benchmark requiring external knowledge","venue":null,"work_id":"e95f125f-4c52-4db6-9d80-c973a27e1da5","year":2019},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:a94e71c5d10ef0bc0018a2e07844bb9384c0b219fdba0e9351f6db23f9140482","observation_id":"fdb8cea0-1516-49fc-819e-f97320758ee7","resolution":{"observed_at":"2026-05-16T15:27:04.524503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.10244","last_updated":"2022-03-19T05:00:30Z","snapshot_observed_at":"2026-08-11T03:45:43.920485Z","submitted_at":"2022-03-19T05:00:30Z","title":"ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning","version":1},"cited_work":{"arxiv_id":"2203.10244","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.10244","snapshot_observed_at":"2026-07-04T16:39:57.602645Z","title":"ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning","venue":"cs.CL","work_id":"8b49b78c-7e1d-4f57-af10-7c11cd63ff7c","year":2022},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2203.10244","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:2ce0dbcf7283007699c99701a7f642cc883bf58fe4b24d500c9f515621fe1aa3","observation_id":"d980d303-9e68-4766-b295-b7fe3bbb59a8","resolution":{"observed_at":"2026-05-16T15:27:04.424149Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Llama 3.2: Revolutionizing edge AI and vision with open, customizable models","venue":null,"work_id":"d9bfe4de-5398-442e-9cd9-089b61558abd","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b821b9518942227fee207772e7167424c9405b077fcfb1c6641a702ad07ece2c","observation_id":"62c01d96-d11a-4d4b-bdb2-723e790f1748","resolution":{"observed_at":"2026-05-16T15:27:04.526813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09332","last_updated":"2022-06-01T19:08:11Z","snapshot_observed_at":"2026-08-07T17:14:39.278754Z","submitted_at":"2021-12-17T05:43:43Z","title":"WebGPT: Browser-assisted question-answering with human feedback","version":3},"cited_work":{"arxiv_id":"2112.09332","doi":"10.48550/arxiv.2112.09332","metadata_source":"pith","pith_arxiv_id":"2112.09332","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"WebGPT: Browser-assisted question-answering with human feedback","venue":"cs.CL","work_id":"e25ef3e1-4848-4cb9-bf28-67a420591165","year":2021},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2112.09332","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:7077be1141bb4a970b724a08b8c54396c5ec27be70f3f40f323762d8d69c5ec7","observation_id":"9d5b7531-ca6e-4a28-a2a4-395b39d75f69","resolution":{"observed_at":"2026-05-16T15:27:04.431295Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-04T01:08:09.995583+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-04T01:08:09.995583+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Introducing deep research","venue":null,"work_id":"88445e1e-d14a-4046-baea-3a8ca5c2b7af","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:7e81a0c0dd9145fb891829aa91816f1c0b24870398cb9541534c5c058a2254c5","observation_id":"429f3f93-b749-4c82-87f6-c621b72694f8","resolution":{"observed_at":"2026-05-16T15:27:04.528923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"OpenAI o3 and o4-mini System Card","venue":null,"work_id":"fbb12269-ac98-49b6-be68-26784bcff26f","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:f679f9b64ca08582a100c4a79df46fb96a065afe6534e2dcd5654b379430bc48","observation_id":"9217ac73-fd86-42d8-a4bc-2d76cba87676","resolution":{"observed_at":"2026-05-16T15:27:04.530986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Introducing Perplexity Deep Research","venue":null,"work_id":"fd3c0996-7ef3-45e5-9e94-9576f75469e3","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:4f34ba664e56691678a85806b69aaf6d6c9a5623ab3460fe9b3c33bd15151192","observation_id":"5c7a378a-c1b1-4814-8921-00f116ab7308","resolution":{"observed_at":"2026-05-16T15:27:04.532996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Qwen3: Think Deeper, Act Faster","venue":null,"work_id":"59134c18-b589-4f55-9179-f4b67713697e","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:1f74f12e2161611bf3c4ec64c126d046ceb988e35b43e4b2a1b4f9892487c2c5","observation_id":"df098708-462f-4788-a250-9d009544b528","resolution":{"observed_at":"2026-05-16T15:27:04.535101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"58497e5a-c16d-41a8-9e8a-5620b5fb289e","year":2021},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:3d5a0195bc152e0a0173d0b8426f3586037564261a4080af8c9ce52cbcfe75ad","observation_id":"a1992e64-7f36-472d-a59d-36d015b336c7","resolution":{"observed_at":"2026-05-16T15:27:04.537234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Toolformer: Language models can teach themselves to use tools","venue":null,"work_id":"b90ad3af-0f3e-47e4-b55d-25687b828d68","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:1e476cb7906b4e092ab1a11be4ad35c749bccfbbb9760a5699ec14d418e8481d","observation_id":"803e8584-7609-4217-afca-c4df22630c5c","resolution":{"observed_at":"2026-05-16T15:27:04.539203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":"1707.06347","doi":"10.1016/j.artint.2010.12.005","metadata_source":"pith","pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Proximal Policy Optimization Algorithms","venue":"cs.LG","work_id":"240c67fe-d14d-4520-91c1-38a4e272ca19","year":2017},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:0e69adb264388ea757d74c0b564b353cf526ea002a9ab4e514ae83f608638f22","observation_id":"86456fad-f86c-4f56-b3b7-81eae666eb02","resolution":{"observed_at":"2026-05-16T15:27:04.283567Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15294","last_updated":"2023-10-23T09:58:13Z","snapshot_observed_at":"2026-08-03T16:18:57.922065Z","submitted_at":"2023-05-24T16:17:36Z","title":"Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy","version":2},"cited_work":{"arxiv_id":"2305.15294","doi":"10.48550/arxiv.2305.15294","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15294","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy","venue":"arXiv (Cornell University)","work_id":"0826d81f-256a-4b75-b51f-e008603cc3e6","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2305.15294","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:f9fd99e7eb623dc38444af65294028acb44812e5d7d4c0d4a014e48cd5cd9d26","observation_id":"028aeb9c-6a8d-4c19-b596-7772ec9390e5","resolution":{"observed_at":"2026-05-16T15:27:04.288985Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":"2402.03300","doi":"10.1016/0004-3702(73)90011-8","metadata_source":"pith","pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","venue":"cs.CL","work_id":"c5006563-f3ec-438a-9e35-b7b484f34828","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:08873babcdda752c13c49f1a92e97d8b84b5371bfb14c1ee6817b8150f9095c9","observation_id":"bf74a1a0-a579-4018-bde3-ffe8239dd37f","resolution":{"observed_at":"2026-05-16T15:27:04.293465Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19256","last_updated":"2024-10-02T04:01:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-28T06:20:03Z","title":"HybridFlow: A Flexible and Efficient RLHF Framework","version":2},"cited_work":{"arxiv_id":"2409.19256","doi":"10.1145/3689031.3696075.url:","metadata_source":"pith","pith_arxiv_id":"2409.19256","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"HybridFlow: A Flexible and Efficient RLHF Framework","venue":"cs.LG","work_id":"7eb9c9f4-b322-4bba-8011-09ff8d6ad801","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2409.19256","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6547f8ec829a24dce038f8756d2d3bbc428fe68bb971d5aac96e3431282b7d35","observation_id":"7bda4ffc-1e9b-4a2f-b809-8161f02d7a53","resolution":{"observed_at":"2026-05-16T15:27:04.297908Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":"2312.11805","doi":"10.1038/nrn2888","metadata_source":"pith","pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Gemini: A Family of Highly Capable Multimodal Models","venue":"cs.CL","work_id":"83f7c85b-3f11-450f-ac0c-64d9745220b2","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:f92cefc9c5961de26dc1f1cddea267db24779b49a54d06d0e720e03b0dffc7df","observation_id":"9cab197d-041f-4016-8456-b654faa25a3e","resolution":{"observed_at":"2026-05-16T15:27:04.302160Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12599","last_updated":"2025-06-03T02:14:54Z","snapshot_observed_at":"2026-08-11T01:31:26.242281Z","submitted_at":"2025-01-22T02:48:14Z","title":"Kimi k1.5: Scaling Reinforcement Learning with LLMs","version":4},"cited_work":{"arxiv_id":"2501.12599","doi":"10.48550/arxiv.2501.12599","metadata_source":"pith","pith_arxiv_id":"2501.12599","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Kimi k1.5: Scaling Reinforcement Learning with LLMs","venue":"cs.AI","work_id":"bff96ab1-bd6a-4585-be23-74fdb51969c7","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2501.12599","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:26da267e31361d5a86034e90fd8370583ad9ddf09fdc423e8a2466cc929a2a93","observation_id":"72d823a9-7154-4c18-9dbd-b136a94a75e3","resolution":{"observed_at":"2026-05-16T15:27:04.306580Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-07-09T10:48:38.585868+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T10:48:38.585868+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.07491","last_updated":"2025-06-23T13:45:50Z","snapshot_observed_at":"2026-08-09T09:48:45.884814Z","submitted_at":"2025-04-10T06:48:26Z","title":"Kimi-VL Technical Report","version":3},"cited_work":{"arxiv_id":"2504.07491","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.07491","snapshot_observed_at":"2026-07-08T06:34:41.884360Z","title":"Kimi-VL Technical Report","venue":"cs.CV","work_id":"c876520f-8a20-44f3-b92a-bf7d35bd430f","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2504.07491","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:26f05deda6972a7eb106758a8ec696191163758a30335ac00ebf95f59fe6ac01","observation_id":"9556cc53-a69b-4904-92f2-650f750ec813","resolution":{"observed_at":"2026-05-16T15:27:04.310839Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07713","last_updated":"2024-05-29T04:15:39Z","snapshot_observed_at":"2026-08-11T10:08:10.605467Z","submitted_at":"2023-10-11T17:59:05Z","title":"InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining","version":3},"cited_work":{"arxiv_id":"2310.07713","doi":"10.48550/arxiv.2310.07713","metadata_source":"arxiv_reference","pith_arxiv_id":"2310.07713","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Instructretro: Instruction tuning post retrieval-augmented pre- training","venue":"arXiv (Cornell University)","work_id":"1a118296-ef03-45c8-bdab-b4268f23b29a","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2310.07713","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:abb9e31cc3b4dcb939cd56bf0bb03b40ea526d04c6c752a5b81d29a06be37e2d","observation_id":"6f006898-0642-44de-ac32-d48b7cb8d6c9","resolution":{"observed_at":"2026-05-16T15:27:04.315830Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mdr: Model-specific demonstration retrieval at inference time for in-context learning","venue":null,"work_id":"3006b088-4374-4a92-9ed5-a1427866cbb4","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b5e5c73fa4f705ed8748885fc66ae9f9d67b28ab3792920d80551b887acbb260","observation_id":"e92d8234-e30e-4881-b300-e43b659d7b87","resolution":{"observed_at":"2026-05-16T15:27:04.541548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07617","last_updated":"2026-05-31T18:45:03Z","snapshot_observed_at":"2026-08-08T12:06:14.483667Z","submitted_at":"2025-02-11T15:05:33Z","title":"Scaling Pre-training to One Hundred Billion Data for Vision Language Models","version":2},"cited_work":{"arxiv_id":"2502.07617","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.07617","snapshot_observed_at":"2026-07-04T00:49:19.193120Z","title":"Scaling pre-training to one hundred billion data for vision language models.arXiv preprint arXiv:2502.07617, 2025a","venue":"cs.CV","work_id":"368c410b-8396-411d-b445-36d9f0f44537","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2502.07617","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:e6f1a43d5fd2cba8749ce91164d2e0158a23e97d961a334815ac8706e8a0a1f2","observation_id":"88ae1726-3604-42ef-aef6-8e719bafce47","resolution":{"observed_at":"2026-06-02T03:03:58.670309Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16671","last_updated":"2025-11-23T00:34:43Z","snapshot_observed_at":"2026-08-02T18:24:11.208164Z","submitted_at":"2023-09-28T17:59:56Z","title":"Demystifying CLIP Data","version":6},"cited_work":{"arxiv_id":"2309.16671","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.16671","snapshot_observed_at":"2026-07-04T20:50:12.667951Z","title":"Demystifying CLIP Data","venue":"cs.CV","work_id":"7af932a5-c6d2-4f55-9522-7777cc3fa5ae","year":2023},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2309.16671","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b573b2e448f057db927f0ccf43a22331600923e9a3a67db7b4f1aa1ae2de29b4","observation_id":"0998698a-d935-465a-a0df-92da4873bb6b","resolution":{"observed_at":"2026-05-16T15:27:04.328458Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10594","last_updated":"2025-03-02T01:19:51Z","snapshot_observed_at":"2026-08-10T05:52:50.722724Z","submitted_at":"2024-10-14T15:04:18Z","title":"VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents","version":2},"cited_work":{"arxiv_id":"2410.10594","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.10594","snapshot_observed_at":"2026-07-03T05:57:41.459329Z","title":"VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents","venue":"cs.IR","work_id":"91acd90a-d182-4502-a92c-390a77f29b81","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2410.10594","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:1344bc75f7c6791a2891ce17fff6ca17f802ea7c1ece688aa48f28e089de2a68","observation_id":"21cc2032-b821-455d-a7cb-103068b83011","resolution":{"observed_at":"2026-05-16T15:37:25.955223Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rankrag: Unifying context ranking with retrieval-augmented generation in llms","venue":null,"work_id":"03928c09-b176-4a13-8fdf-dc58fcb05fc4","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:3f0d4bb9553986b1155b8262eaa92de09bcbdb7a8feeee3274d9b3a0ca2df974","observation_id":"b93e182a-e70d-47ff-92e4-2bb54b22a1a5","resolution":{"observed_at":"2026-05-16T15:27:04.543441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12772","last_updated":"2025-05-05T04:48:45Z","snapshot_observed_at":"2026-07-06T18:47:56.109836Z","submitted_at":"2024-07-17T17:51:53Z","title":"LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models","version":2},"cited_work":{"arxiv_id":"2407.12772","doi":"10.48550/arxiv.2407.12772","metadata_source":"pith","pith_arxiv_id":"2407.12772","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models","venue":"cs.CL","work_id":"257da118-790b-4686-87d7-92321d7e1ae0","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2407.12772","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:dff537a8b1a0bcc1b7cddd91f75025efcb2171c912aa1afe4ee385b6a419476c","observation_id":"3ca77f38-1b04-454e-b51f-3d1e2a2bf5e2","resolution":{"observed_at":"2026-05-17T05:19:22.513527Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Raft: Adapting language model to domain specific rag","venue":null,"work_id":"ee8ff381-8799-445f-bf5a-b2ee1afbdbad","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:1cf2e6351a55251961cc2d06c972cba395dc85ee42b0703692c94aede92f70fc","observation_id":"c8295a8f-46fc-4162-9792-c5525caf68fc","resolution":{"observed_at":"2026-05-16T15:27:04.545344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.00958","last_updated":"2025-05-13T16:29:08Z","snapshot_observed_at":"2026-08-11T03:06:20.615484Z","submitted_at":"2025-01-01T21:29:37Z","title":"2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining","version":4},"cited_work":{"arxiv_id":"2501.00958","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.00958","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"2.5 years in class: A multimodal textbook for vision-language pretraining","venue":null,"work_id":"0c24ef2e-2a71-4a48-8d77-55f8efbc2e06","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2501.00958","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:41824b14e0055317bcfd29dc9202631dc3a6c7b21a74949d26612aabf94aaea8","observation_id":"07cc1ea5-4d39-47ed-aa23-194287dc94d8","resolution":{"observed_at":"2026-05-16T15:27:04.350557Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02713","last_updated":"2025-08-01T16:40:14Z","snapshot_observed_at":"2026-08-02T12:24:31.329178Z","submitted_at":"2024-10-03T17:36:49Z","title":"LLaVA-Video: Video Instruction Tuning With Synthetic Data","version":3},"cited_work":{"arxiv_id":"2410.02713","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.02713","snapshot_observed_at":"2026-07-09T21:36:34.348434Z","title":"LLaVA-Video: Video Instruction Tuning With Synthetic Data","venue":"cs.CV","work_id":"e598f516-d992-449a-ab6d-6c788b3a1d7b","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2410.02713","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6153496c322db5f89c9f30879b2cea6e73a03f174479e621305a42c3d9183e29","observation_id":"2d883cd6-d552-4a7f-a565-86d5b4dc3436","resolution":{"observed_at":"2026-05-16T15:27:04.354589Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21220","last_updated":"2024-10-28T17:04:18Z","snapshot_observed_at":"2026-08-11T08:31:14.561578Z","submitted_at":"2024-10-28T17:04:18Z","title":"Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines","version":1},"cited_work":{"arxiv_id":"2410.21220","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.21220","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vision search assistant: Em- power vision-language models as multimodal search engines","venue":null,"work_id":"b8776ac3-ff10-4830-8639-e5200cb5cb19","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2410.21220","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:ec4785fae5272ba3291ef56ebfbcabb3fe5c10d29dc0630e26e4177607a28ca2","observation_id":"fdd8921a-fe0a-40e5-b704-e73f448640eb","resolution":{"observed_at":"2026-05-16T15:27:04.359334Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.13372","last_updated":"2024-06-27T22:44:48Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-03-20T08:08:54Z","title":"LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models","version":4},"cited_work":{"arxiv_id":"2403.13372","doi":"10.48550/arxiv.2403.13372","metadata_source":"pith","pith_arxiv_id":"2403.13372","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models","venue":"cs.CL","work_id":"462b3287-e058-48e3-b5e3-82a5f2a8dc06","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2403.13372","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:cbac4b4d3afdbdda3b1a751dcfe2e4ac4b2d2a231455f0d4e554adaef227e0d7","observation_id":"ee0dbc75-df81-4138-b16f-fd709ff2ce15","resolution":{"observed_at":"2026-05-16T15:27:04.363149Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.03160","last_updated":"2025-04-17T04:46:08Z","snapshot_observed_at":"2026-07-06T21:04:06.413573Z","submitted_at":"2025-04-04T04:41:28Z","title":"DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments","version":4},"cited_work":{"arxiv_id":"2504.03160","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.03160","snapshot_observed_at":"2026-07-03T04:37:37.738752Z","title":"DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments","venue":"cs.AI","work_id":"460d8021-a193-45c3-89a7-b72f6767c87f","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2504.03160","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:8ad3ffcebc5807702d459c7db81131e990ae2575b38722e509c52e06e6789c07","observation_id":"e8d6990d-a15c-463b-8369-11ea44ac6ce5","resolution":{"observed_at":"2026-05-16T19:58:59.023888Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mitchell is best known for designing the Supermarine Splitfire","venue":null,"work_id":"8148d278-e076-4be0-a793-b8f43c03b846","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:9109883b7dca7fee2260e441fad41114e50b83499893434ac3410abae4d03101","observation_id":"b84d9fb7-b5f7-40fc-8e35-9ef676aa2f15","resolution":{"observed_at":"2026-05-16T15:27:04.547657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Search Results Figure 6: The overall architecture of the multimodal search pipeline","venue":null,"work_id":"39ca37d4-1389-491b-a757-0d0204ade7ad","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:3d1ff84100feeb136c613c9ee3cf9049a6c6605d57e9249b14ef2d5e236b1920","observation_id":"39a3a04f-50cd-4a9d-9364-5cfe8d54e258","resolution":{"observed_at":"2026-05-16T15:27:04.549847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"bcff8988-d792-42f5-8db2-b67cb6be9483","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:802e2ed426f26dbf5d8eb2c794ca8008a9a073a475d945a86cc75c72b3b5716b","observation_id":"9d72719e-9396-4de2-b89d-bc10ff0f284a","resolution":{"observed_at":"2026-05-16T15:27:04.551788Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Who\", \"What","venue":null,"work_id":"e70c796a-deca-4110-a30a-1bd8ed87d6ab","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:47d3fceb71362c1ff4a56eaa7a61c404f61a78005db1299e77788d0da58b3a99","observation_id":"63b9ba00-cf40-47b8-99ca-e0b67afa820e","resolution":{"observed_at":"2026-05-16T15:27:04.553915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"780d23ba-1123-4051-95c3-6c3b3e404c04","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:11b99ff4900aa0e4b7465af5d85e5182b62198f55a7507d301daadada4918f33","observation_id":"1a990430-1aa6-4d6c-90fb-23fafc51a7ec","resolution":{"observed_at":"2026-05-16T15:27:04.556019Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Unable to answer due to lack of relevant information","venue":null,"work_id":"150a74b1-32c1-4f16-8d5d-de8ccfb17123","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:1d52c0df9ac7df88c7326af02907ca2a79874fbcb5e7c97b1f9012faf7966ad5","observation_id":"400d2352-aa2a-4bb7-9270-bde5c15fe2c3","resolution":{"observed_at":"2026-05-16T15:27:04.558140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"6a195092-6da4-4dc3-bdb0-e5f33208b46d","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:f09eb5390eac0209b5c9653c3f49368e978f142f85d36f958e1c1c7107d3c048","observation_id":"d838226e-2b8d-4356-886d-88d1afe6ec64","resolution":{"observed_at":"2026-05-16T15:27:04.559921Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Based on the question, image and image search results, please raise a text query to the search engine to search for what is useful for you to answer the question correctly","venue":null,"work_id":"ca387c13-e519-4b6c-8c86-13640d1d0e7d","year":2000},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:d0f42e4ad23e169956973c21a59cd377b07aaff93a4d52f567423dde181c2bb3","observation_id":"0c382608-1728-486c-937f-8b65d6083744","resolution":{"observed_at":"2026-05-16T15:27:04.562036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"2d81ef54-ee15-45c8-8592-b6347662024a","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:8e959fd6fe8417536a74e6a5f783356745fdd0a3338cc0a017c12b3a1ad0e373","observation_id":"1feb88da-d221-4488-ad94-f17776edde04","resolution":{"observed_at":"2026-05-16T15:27:04.564086Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"190cfcdc-bede-43da-9c8a-ba2f54869422","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:99edbc03d1ad4251b652baf153247eb9791842e876fafbf2a047ab2b39c5b6fa","observation_id":"036511ca-2ffd-4690-9347-962f529ea73c","resolution":{"observed_at":"2026-05-16T15:27:04.566097Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a142d643-3859-441f-99a2-71536c6de083","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:98a69bcf6e21ca3a41dfd4506af594e80e42e71e1e2be98696b77ac17610a87e","observation_id":"c3561c88-f8e4-4bd9-b313-4d6df7d69b0c","resolution":{"observed_at":"2026-05-16T15:27:04.568128Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e91292bf-b26f-4884-b6d6-0a6ad912b12b","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:2cc6cfec038b304b57ef4d8c2b8eb64eeeb978e0b7ee87991c610d217f4eed65","observation_id":"397e8a3c-918f-43c2-ab3f-ae8126a00468","resolution":{"observed_at":"2026-05-16T15:27:04.570194Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f418259d-76d8-4b85-b73c-42a99d5c1d39","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:6ad801779ecbe11b2a7b93c5288bbb7813f49e275e773a13402902b35d94a90e","observation_id":"314f5f89-7053-4ab1-9eac-6b389aacd553","resolution":{"observed_at":"2026-05-16T15:27:04.572257Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"a09892a4-a6da-4af1-a8fa-32e4dc54868d","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b24608358b072b6c68f6f9c3c81a2bf76683b6b868ca56e53369b9124a552496","observation_id":"3ba4e51a-9802-43ca-9678-ca4a07111fb5","resolution":{"observed_at":"2026-05-16T15:27:04.456389Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"If the middle name is extra but correct, consider it correct","venue":null,"work_id":"44224df0-57a7-4bfa-a605-cf90d5bcb0d5","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:e12aa4d91a19939cb46dfc57bffcd13ba95f1072ecef6622d9dc9d3f783ffee9","observation_id":"eca017ae-ed86-45e5-abc8-d88d4e2a035f","resolution":{"observed_at":"2026-05-16T15:27:04.459462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Yes\" or","venue":null,"work_id":"35ce9781-77ce-464e-ae5a-719a9077dff4","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:8f23c7195fcadb127b692f7d6b6418d1926468a1d63c3fc5967015a832211f7c","observation_id":"4e81e160-b98a-4fcc-a949-ce3ad411c376","resolution":{"observed_at":"2026-05-16T15:27:04.461958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Refer to the image only when necessary to minimize misjudgment","venue":null,"work_id":"3dd1081e-c0a4-46fa-b186-f3a11b42d7f6","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b241ff1262c5c261768fbce72cd111fbb8cfe3a4a33fc64d56f42413cab359f6","observation_id":"d8290bef-6083-4773-95bb-6414b90f2571","resolution":{"observed_at":"2026-05-16T15:27:04.464632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"If the response aligns with at least one candidate according to the rules above, it should be considered correct","venue":null,"work_id":"7b2cebd3-e9ac-470e-9dd7-9fb013e5f511","year":null},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:00c56ac1f01e4c73902106ae20111dcd09b9f04fc4ff70637e8b1e05b9251b91","observation_id":"5bd03ea3-c6f2-4f4a-8d70-3f5eb8027309","resolution":{"observed_at":"2026-05-16T15:27:04.467049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Yes\" or","venue":null,"work_id":"93d8f5b7-66a0-496f-90ac-9f118f1235e0","year":2020},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b5eff94a516da82150375d83b9c9b224a1560dcfe09ad06d3c19eb5a01c882e8","observation_id":"c21af0b9-58cf-4941-86bb-8b4cfcf47937","resolution":{"observed_at":"2026-05-16T15:27:04.469207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The decision followed a comprehensive internal review","venue":null,"work_id":"cb478c18-8ba7-4a9c-bcdd-943404e42f52","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:c963bb118bef29e96745c7fc751658f3be1e0941c783f32a71162bb1119d0873","observation_id":"52ec12e4-c394-4bc1-bfc4-9b4c4f5a46e0","resolution":{"observed_at":"2026-05-16T15:27:04.471913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Following this cancellation","venue":null,"work_id":"fd7b7926-0c99-4895-a6b5-f879176caa43","year":2025},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:b14eb4bf1b6e27dac4283cba3c6fbb0153972345cc3d7bdc60036f146be0221c","observation_id":"7f3e60f7-d74e-42bc-a674-350645dbb58f","resolution":{"observed_at":"2026-05-16T15:27:04.474020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Battle of Flodden","venue":null,"work_id":"5aeeff0e-be96-4390-8206-abcc39d6c8c2","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:48ed69c71c2e7e59561f1260076361807bd41a9f42f30ecc5924b30bfd82a3ef","observation_id":"52428244-a452-4e58-91b2-5f0abc2e9683","resolution":{"observed_at":"2026-05-16T15:27:04.476233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search"},"reference_resolution":{"displayed":94,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":9,"verified_exact":42,"verified_fuzzy":42},"total_outbound_references":94},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 49 inbound Pith citation observations for arXiv:2506.20670."}