{"as_of":"2026-08-08T05:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:04425d11e554ffa942e2383ef71a5498686a03e3e7fa4cd73afdf6fd9ecc9d47","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:43:43.270853Z","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":"2026-07-03T17:18:43.847565Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2204.13653","last_updated":"2022-05-02T19:26:41Z","snapshot_observed_at":"2026-08-03T08:52:08.086658Z","submitted_at":"2022-04-28T17:13:23Z","title":"GRIT: General Robust Image Task Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.13653","snapshot_observed_at":"2026-08-07T04:43:43.270853Z","title":"Grit: General robust image task benchmark","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.09954","last_updated":"2025-06-11T17:23:41Z","snapshot_observed_at":"2026-08-07T21:45:10.885875Z","submitted_at":"2025-06-11T17:23:41Z","title":"Vision Generalist Model: A Survey","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-07T04:43:43.270853Z"},"links":{"cited_paper":"/paper/2204.13653","citing_paper":"/paper/2506.09954"},"observation_digest":"sha256:1f9bac88e63bbca8728dd016dc3e27e0b1ab7c31c43614c06e9839afb30b9fa3","observation_id":"94e049cb-e175-4c4b-84bd-d7ed481aa2a6","resolution":{"observed_at":"2026-08-07T04:43:43.270853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.13653","last_updated":"2022-05-02T19:26:41Z","snapshot_observed_at":"2026-08-03T08:52:08.086658Z","submitted_at":"2022-04-28T17:13:23Z","title":"GRIT: General Robust Image Task Benchmark","version":2},"cited_work":{"arxiv_id":"2204.13653","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.13653","snapshot_observed_at":"2026-07-03T17:18:43.847565Z","title":"arXiv:2204.13653 , year=","venue":null,"work_id":"f2935802-e3d7-4e29-9b09-7d73b2914784","year":2022},"citing_paper":{"arxiv_id":"2606.17030","last_updated":"2026-06-17T13:54:57Z","snapshot_observed_at":"2026-08-01T21:48:31.832288Z","submitted_at":"2026-06-15T17:52:31Z","title":"Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation","version":3},"reference_index":152,"source":"arxiv_source","source_observed_at":"2026-06-27T04:19:26.332718Z"},"links":{"cited_paper":"/paper/2204.13653","citing_paper":"/paper/2606.17030"},"observation_digest":"sha256:763c03992cdd20b62ad8ec365cd483a3ceaf60b4f6e5457ec4d8aa3445623801","observation_id":"6a1d1e9a-5e57-4727-8875-599fb0bc97c0","resolution":{"observed_at":"2026-07-03T17:18:43.849310Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.13653","last_updated":"2022-05-02T19:26:41Z","snapshot_observed_at":"2026-08-03T08:52:08.086658Z","submitted_at":"2022-04-28T17:13:23Z","title":"GRIT: General Robust Image Task Benchmark","version":2},"cited_work":{"arxiv_id":"2204.13653","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.13653","snapshot_observed_at":"2026-07-03T17:18:43.847565Z","title":"arXiv:2204.13653 , year=","venue":null,"work_id":"f2935802-e3d7-4e29-9b09-7d73b2914784","year":2022},"citing_paper":{"arxiv_id":"2607.00338","last_updated":"2026-07-01T02:27:40Z","snapshot_observed_at":"2026-08-07T09:28:37.215060Z","submitted_at":"2026-07-01T02:27:40Z","title":"DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-02T15:23:42.245556Z"},"links":{"cited_paper":"/paper/2204.13653","citing_paper":"/paper/2607.00338"},"observation_digest":"sha256:7c47242358931156f559c830b0fe6c1c92fe0934d81640788203c86ef75821f7","observation_id":"e20c79b0-218a-4deb-927b-abd48627f3a4","resolution":{"observed_at":"2026-07-02T15:27:04.700501Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.13653","last_updated":"2022-05-02T19:26:41Z","snapshot_observed_at":"2026-08-03T08:52:08.086658Z","submitted_at":"2022-04-28T17:13:23Z","title":"GRIT: General Robust Image Task Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.13653","snapshot_observed_at":"2026-07-14T03:31:19.309532Z","title":"arXiv:2204.13653 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11738","last_updated":"2026-07-13T16:00:03Z","snapshot_observed_at":"2026-08-06T12:36:13.363835Z","submitted_at":"2026-07-13T16:00:03Z","title":"Qwen-Audio-VAE Technical Report","version":1},"reference_index":167,"source":"arxiv_source","source_observed_at":"2026-07-14T03:31:19.309532Z"},"links":{"cited_paper":"/paper/2204.13653","citing_paper":"/paper/2607.11738"},"observation_digest":"sha256:6c5767fd8fab8d83a1173dc4623a754fe64241cb87ea61f453a2fcd7ed56f52d","observation_id":"1140653f-d00a-43f6-801c-63116419c985","resolution":{"observed_at":"2026-07-14T03:31:19.309532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2204.13653/citation-record","integrity":"/paper/2204.13653/integrity","json":"/paper/2204.13653/citation-record.json","paper":"/paper/2204.13653"},"outbound":[],"paper":{"arxiv_id":"2204.13653","last_updated":"2022-05-02T19:26:41Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-03T08:52:08.086658Z","submitted_at":"2022-04-28T17:13:23Z","title":"GRIT: General Robust Image Task Benchmark"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2204.13653."}