{"as_of":"2026-08-09T18:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:91daf1352edc357d60d1dc1853d00aac921ce1136f624be59091c8b3b62ab9f3","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:36:14.442972Z","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":"2026-06-30T09:54:35.322765Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-08-06T22:36:14.442972Z","title":"Actionart: Advancing multi- modal large models for fine-grained human-centric video understanding,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.21277","last_updated":"2025-06-26T14:01:03Z","snapshot_observed_at":"2026-08-08T12:42:20.980285Z","submitted_at":"2025-06-26T14:01:03Z","title":"HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.442972Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2506.21277"},"observation_digest":"sha256:5e79d44793a0699a16586c6366f3c1c7173d3cbb444cacd96810df9b318eb4f4","observation_id":"da4ef8b4-87b9-44b4-bb5c-c0544257c32a","resolution":{"observed_at":"2026-08-06T22:36:14.442972Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-08-06T20:53:20.338147Z","title":"Ac- tionart: Advancing multimodal large models for fine- grained human-centric video understanding","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01492","last_updated":"2025-07-02T08:51:45Z","snapshot_observed_at":"2026-08-09T05:08:35.154237Z","submitted_at":"2025-07-02T08:51:45Z","title":"AVC-DPO: Aligned Video Captioning via Direct Preference Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:53:20.338147Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2507.01492"},"observation_digest":"sha256:b7dcfa316d7f665cbb0fa4b27415d88d134424f219fded25e12a0df2f628b94c","observation_id":"25fe8ebe-aa16-489f-aea8-7827e1cd60b3","resolution":{"observed_at":"2026-08-06T20:53:20.338147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":"2504.18152","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-06-30T09:54:35.322765Z","title":"Ac- tionart: Advancing multimodal large models for fine- grained human-centric video understanding","venue":null,"work_id":"7896d956-c259-4b1c-9449-e0b2c200ff8b","year":2025},"citing_paper":{"arxiv_id":"2604.05079","last_updated":"2026-04-06T18:30:50Z","snapshot_observed_at":"2026-08-02T23:48:40.440218Z","submitted_at":"2026-04-06T18:30:50Z","title":"SVAgent: Storyline-Guided Long Video Understanding via Cross-Modal Multi-Agent Collaboration","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T20:20:08.590407Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2604.05079"},"observation_digest":"sha256:0363ba88ea78a20322e66b5917527c08506a0cffcea892c7f63dc27a2deddddc","observation_id":"f50d51cd-1905-4ed7-b73f-622651c3aa42","resolution":{"observed_at":"2026-05-10T22:00:49.056011Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":"2504.18152","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-06-30T09:54:35.322765Z","title":"Ac- tionart: Advancing multimodal large models for fine- grained human-centric video understanding","venue":null,"work_id":"7896d956-c259-4b1c-9449-e0b2c200ff8b","year":2025},"citing_paper":{"arxiv_id":"2605.28604","last_updated":"2026-05-27T15:20:06Z","snapshot_observed_at":"2026-07-06T23:38:09.179597Z","submitted_at":"2026-05-27T15:20:06Z","title":"Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-29T13:26:21.016303Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2605.28604"},"observation_digest":"sha256:42dbcdad560d9dd678d6793f868038628e4c9ce4e0c441e904e9b41ca6eccf37","observation_id":"690280ac-a2d5-4e5b-b0dc-d60ab562d5e4","resolution":{"observed_at":"2026-06-29T13:33:28.320458Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":"2504.18152","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-06-30T09:54:35.322765Z","title":"Ac- tionart: Advancing multimodal large models for fine- grained human-centric video understanding","venue":null,"work_id":"7896d956-c259-4b1c-9449-e0b2c200ff8b","year":2025},"citing_paper":{"arxiv_id":"2606.27999","last_updated":"2026-06-29T10:15:53Z","snapshot_observed_at":"2026-08-06T16:35:46.841389Z","submitted_at":"2026-06-26T11:52:37Z","title":"HumanMoveVQA: Can Video MLLMs reason about human movement in videos?","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-29T04:53:11.830488Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2606.27999"},"observation_digest":"sha256:732e8d0a4ac91d87809893a4a4d2dddfac3cafac496b181fe241e40c7fe7920c","observation_id":"251ad567-e0b9-480a-9e46-e318d7da0ca8","resolution":{"observed_at":"2026-06-29T19:13:53.056250Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding","version":1},"cited_work":{"arxiv_id":"2504.18152","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18152","snapshot_observed_at":"2026-06-30T09:54:35.322765Z","title":"Ac- tionart: Advancing multimodal large models for fine- grained human-centric video understanding","venue":null,"work_id":"7896d956-c259-4b1c-9449-e0b2c200ff8b","year":2025},"citing_paper":{"arxiv_id":"2606.27999","last_updated":"2026-06-29T10:15:53Z","snapshot_observed_at":"2026-08-06T16:35:46.841389Z","submitted_at":"2026-06-26T11:52:37Z","title":"HumanMoveVQA: Can Video MLLMs reason about human movement in videos?","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T09:46:56.063333Z"},"links":{"cited_paper":"/paper/2504.18152","citing_paper":"/paper/2606.27999"},"observation_digest":"sha256:ab4e1ec959a2a3e7e5ace71b02918399a13cea1cac3b8c560146c12c23db75e1","observation_id":"b58fd2bb-2e51-4fd0-a17a-1a51846e9090","resolution":{"observed_at":"2026-06-30T09:54:35.324230Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.18152/citation-record","integrity":"/paper/2504.18152/integrity","json":"/paper/2504.18152/citation-record.json","paper":"/paper/2504.18152"},"outbound":[],"paper":{"arxiv_id":"2504.18152","last_updated":"2025-04-25T08:05:32Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T15:59:17.660418Z","submitted_at":"2025-04-25T08:05:32Z","title":"ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2504.18152."}