{"as_of":"2026-08-16T04:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ce7a3e94036fea4b0bc7807456e16360ff0c2683a30d292066abf83269843223","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:53:22.565482Z","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":"2026-07-02T07:56:47.326486Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-11T16:51:15.406260Z","title":"Longagent: Scaling language models to 128k context through multi-agent col- laboration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10471","last_updated":"2025-03-10T03:35:16Z","snapshot_observed_at":"2026-08-15T08:24:42.840306Z","submitted_at":"2024-12-12T23:39:54Z","title":"VCA: Video Curious Agent for Long Video Understanding","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T16:51:15.406260Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2412.10471"},"observation_digest":"sha256:a4f6c53034771926b2132669d165df6b571f996cdc39403bf803c9a8c97d5dd5","observation_id":"fecf0dcf-b274-4a34-b8e0-f75cb72ceae1","resolution":{"observed_at":"2026-08-11T16:51:15.406260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-11T05:29:24.657256Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17481","last_updated":"2025-01-07T12:48:22Z","snapshot_observed_at":"2026-08-15T07:26:49.037180Z","submitted_at":"2024-12-23T11:11:51Z","title":"A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application","version":2},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-11T05:29:24.657256Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2412.17481"},"observation_digest":"sha256:8a8228921edd9ed6d7e32c78c2eca5428cff73cabc26bfcf525470462b0488d4","observation_id":"fca512a7-c495-4570-b4a4-dd15b6281d42","resolution":{"observed_at":"2026-08-11T05:29:24.657256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-10T20:33:22.928857Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.08248","last_updated":"2025-06-09T07:37:32Z","snapshot_observed_at":"2026-08-13T12:25:46.254885Z","submitted_at":"2025-01-14T16:38:33Z","title":"Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models","version":3},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-10T20:33:22.928857Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2501.08248"},"observation_digest":"sha256:6d291c7039d9ad0863865c9d8863023e07d4b86959b8fb6ed6cce87cc2af5c82","observation_id":"c0fb0fd3-f755-46ce-9975-d0600d8c78e2","resolution":{"observed_at":"2026-08-10T20:33:22.928857Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-09T19:01:34.608737Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00448","last_updated":"2025-02-01T14:55:06Z","snapshot_observed_at":"2026-08-15T16:37:16.071742Z","submitted_at":"2025-02-01T14:55:06Z","title":"HERA: Improving Long Document Summarization using Large Language Models with Context Packaging and Reordering","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-09T19:01:34.608737Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2502.00448"},"observation_digest":"sha256:2933b8350e46176ddd4e458031d79e67123a8484c118aed53a71a27d412a9a4d","observation_id":"17e74caf-84c7-43e1-a4d3-8b93b7cd0ec4","resolution":{"observed_at":"2026-08-09T19:01:34.608737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-15T20:53:22.565482Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.11811","last_updated":"2025-05-17T03:43:30Z","snapshot_observed_at":"2026-08-15T20:44:57.827841Z","submitted_at":"2025-05-17T03:43:30Z","title":"BELLE: A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-15T20:53:22.565482Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2505.11811"},"observation_digest":"sha256:6003e118cfd55771c528183fbd82e38686f865b1a3f64ac386a61b1b9462c027","observation_id":"a62a3b8a-c90e-4285-af7d-1eac525e9940","resolution":{"observed_at":"2026-08-15T20:53:22.565482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-08-05T15:18:57.713495Z","title":"Longagent: scaling language models to 128k context through multi-agent collaboration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.20018","last_updated":"2025-08-27T16:27:19Z","snapshot_observed_at":"2026-08-15T13:03:03.060918Z","submitted_at":"2025-08-27T16:27:19Z","title":"SWIRL: A Staged Workflow for Interleaved Reinforcement Learning in Mobile GUI Control","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-05T15:18:57.713495Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2508.20018"},"observation_digest":"sha256:b27e7e8f5768af2fbfe5ca4a3098ae52ec7bc825b794af198b7b4ff45d758429","observation_id":"68065708-a7ee-4821-a03d-6e3de2cb1aee","resolution":{"observed_at":"2026-08-05T15:18:57.713495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":"2402.11550","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11550","snapshot_observed_at":"2026-07-02T07:56:47.326486Z","title":"Longagent: scaling language models to 128k context through multi-agent collaboration.arXiv preprint arXiv:2402.11550, 2024","venue":null,"work_id":"e33c1cc9-ceca-46e7-8410-cfed508ba66d","year":2024},"citing_paper":{"arxiv_id":"2606.06532","last_updated":"2026-06-03T17:47:49Z","snapshot_observed_at":"2026-08-15T03:34:25.861188Z","submitted_at":"2026-06-03T17:47:49Z","title":"GOPAgen: Motion-Aware and Efficient Agentic Long-Video Understanding with Structural Memory and Hierarchical Reasoning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-28T06:33:32.090913Z"},"links":{"cited_paper":"/paper/2402.11550","citing_paper":"/paper/2606.06532"},"observation_digest":"sha256:998e491e6d4563a26d34e127ec8d5a37a4f4622651a94aef165e39e68219fb9f","observation_id":"f777e9be-807b-4ef1-ba13-719e1d14d6c6","resolution":{"observed_at":"2026-07-02T07:56:47.328098Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.11550/citation-record","integrity":"/paper/2402.11550/integrity","json":"/paper/2402.11550/citation-record.json","paper":"/paper/2402.11550"},"outbound":[],"paper":{"arxiv_id":"2402.11550","last_updated":"2024-03-13T07:16:42Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T04:16:05.934745Z","submitted_at":"2024-02-18T11:46:52Z","title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2402.11550."}