{"as_of":"2026-08-08T07:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f976a17d20339d4d9d9c23204d0c74d332b60646405b8043711b1a45c75c8d53","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:27:49.827346Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T18:00:26.929675Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.06606","snapshot_observed_at":"2026-08-07T14:27:49.827346Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18831","last_updated":"2025-05-24T19:00:36Z","snapshot_observed_at":"2026-08-07T15:06:24.787553Z","submitted_at":"2025-05-24T19:00:36Z","title":"Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:27:49.827346Z"},"links":{"cited_paper":"/paper/2504.06606","citing_paper":"/paper/2505.18831"},"observation_digest":"sha256:a6d1d8cf66da04e9387c82577b0ea78c36f339aa8a6fe46a8a8ef329eab0b296","observation_id":"cdaeaf76-f5ee-4ca1-9485-b665ec98a63e","resolution":{"observed_at":"2026-08-07T14:27:49.827346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.06606","snapshot_observed_at":"2026-08-07T11:05:19.291846Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.04280","last_updated":"2025-06-04T04:21:32Z","snapshot_observed_at":"2026-08-07T21:26:08.023036Z","submitted_at":"2025-06-04T04:21:32Z","title":"Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:05:19.291846Z"},"links":{"cited_paper":"/paper/2504.06606","citing_paper":"/paper/2506.04280"},"observation_digest":"sha256:40944f8d8052e7602009a4458a173d445986fdab259531e5a420a67c762eb027","observation_id":"87f573ed-96f7-49dc-b444-396ddc047ac6","resolution":{"observed_at":"2026-08-07T11:05:19.291846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.06606","snapshot_observed_at":"2026-08-07T05:02:29.173944Z","title":"Benchmarking multimodal cot reward model stepwise by visual program, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.08933","last_updated":"2025-06-10T15:59:38Z","snapshot_observed_at":"2026-08-07T04:56:29.533924Z","submitted_at":"2025-06-10T15:59:38Z","title":"What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T05:02:29.173944Z"},"links":{"cited_paper":"/paper/2504.06606","citing_paper":"/paper/2506.08933"},"observation_digest":"sha256:817577e8bc3fda7189a720aa92310dc688acabcdf792f346b73a6d27936227b7","observation_id":"37941295-095e-4a19-ba50-e32226ef34bb","resolution":{"observed_at":"2026-08-07T05:02:29.173944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program","version":1},"cited_work":{"arxiv_id":"2504.06606","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.06606","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Benchmarking multimodal cot re- ward model stepwise by visual program","venue":null,"work_id":"b7950d5c-7879-4306-abdc-2310a22a2e97","year":2025},"citing_paper":{"arxiv_id":"2511.23253","last_updated":"2026-05-17T14:28:57Z","snapshot_observed_at":"2026-08-02T03:33:31.761191Z","submitted_at":"2025-11-28T15:02:19Z","title":"AgroCoT: A Chain-of-Thought Benchmark for Evaluating Reasoning in Vision-Language Models for Agriculture","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-21T17:59:42.921867Z"},"links":{"cited_paper":"/paper/2504.06606","citing_paper":"/paper/2511.23253"},"observation_digest":"sha256:fecde3a22750258f6f2bdce4a2d7ddc0e19b9c335bac4aa0b527441b97c58a72","observation_id":"5e2a78c8-16c3-4877-867f-ac7c409d7be8","resolution":{"observed_at":"2026-05-21T18:00:26.932078Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program","version":1},"cited_work":{"arxiv_id":"2504.06606","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.06606","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Benchmarking multimodal cot re- ward model stepwise by visual program","venue":null,"work_id":"b7950d5c-7879-4306-abdc-2310a22a2e97","year":2025},"citing_paper":{"arxiv_id":"2604.13029","last_updated":"2026-04-14T17:58:22Z","snapshot_observed_at":"2026-07-06T23:01:05.634599Z","submitted_at":"2026-04-14T17:58:22Z","title":"Visual Preference Optimization with Rubric Rewards","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-10T15:45:52.980881Z"},"links":{"cited_paper":"/paper/2504.06606","citing_paper":"/paper/2604.13029"},"observation_digest":"sha256:a94392af1ae9676f6e751345aa74ae96a698189f6804f9a61d34bace3e82acde","observation_id":"03c3fede-6045-4704-863d-b0843e11d9fa","resolution":{"observed_at":"2026-05-11T09:56:00.714753Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.06606/citation-record","integrity":"/paper/2504.06606/integrity","json":"/paper/2504.06606/citation-record.json","paper":"/paper/2504.06606"},"outbound":[],"paper":{"arxiv_id":"2504.06606","last_updated":"2025-04-09T06:09:40Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T16:07:18.452869Z","submitted_at":"2025-04-09T06:09:40Z","title":"Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.06606."}