{"as_of":"2026-08-15T17:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dd1297ccdd8644895f8ec92a952c8b5dd454346f04dd2b6aa76853e9da8d0357","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:15:09.545300Z","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":"2026-07-04T00:59:19.505966Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":"2402.00847","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-07-04T00:59:19.505966Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":"e871da74-3c80-4569-81d7-7c47cef2c94b","year":2024},"citing_paper":{"arxiv_id":"2409.01652","last_updated":"2024-11-12T04:33:26Z","snapshot_observed_at":"2026-07-29T23:37:00.228879Z","submitted_at":"2024-09-03T06:45:22Z","title":"ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulation","version":2},"reference_index":146,"source":"pdf_text","source_observed_at":"2026-05-16T08:25:17.847571Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2409.01652"},"observation_digest":"sha256:26a3a9e0ddb725b64bb9edac3b2b4f6f568cffa34c7a06ee944ce351bf448a0d","observation_id":"3c6b50c2-f0cf-4dee-814b-dc8d697f94d2","resolution":{"observed_at":"2026-05-16T08:25:18.117226Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":"2402.00847","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-07-04T00:59:19.505966Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":"e871da74-3c80-4569-81d7-7c47cef2c94b","year":2024},"citing_paper":{"arxiv_id":"2409.16283","last_updated":"2024-09-24T17:57:33Z","snapshot_observed_at":"2026-08-15T00:36:59.684390Z","submitted_at":"2024-09-24T17:57:33Z","title":"Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-15T12:17:01.294466Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2409.16283"},"observation_digest":"sha256:cff25acbce32b325d9e2a13066b894c476140450a11853d3290437a0d2e424d0","observation_id":"c3296676-0b29-49fd-851d-9668b305ccaf","resolution":{"observed_at":"2026-05-15T12:17:01.380972Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-11T23:15:09.545300Z","title":"BootsTAP: Boot- strapped training for tracking-any-point","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02700","last_updated":"2025-03-27T21:38:09Z","snapshot_observed_at":"2026-08-15T08:14:12.017325Z","submitted_at":"2024-12-03T18:59:56Z","title":"Motion Prompting: Controlling Video Generation with Motion Trajectories","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T23:15:09.545300Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2412.02700"},"observation_digest":"sha256:2a5f40b6b8e340c9ae3ddd88e0cc2d68115b63a1d7302affde596058d8191f51","observation_id":"20c2f11f-13c0-4b62-a795-18d7a900ac78","resolution":{"observed_at":"2026-08-11T23:15:09.545300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-11T22:56:27.022395Z","title":"arXiv preprint arXiv:2402.00847 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03021","last_updated":"2025-07-21T07:46:16Z","snapshot_observed_at":"2026-08-15T17:17:00.283717Z","submitted_at":"2024-12-04T04:24:15Z","title":"PEMF-VTO: Point-Enhanced Video Virtual Try-on via Mask-free Paradigm","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T22:56:27.022395Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2412.03021"},"observation_digest":"sha256:3feccc0df7bcae9fbe54191cbcd1745f483a3a10a6a3dbbedbcae41f999bacaf","observation_id":"3fc2073c-4ab2-4fc5-9ef5-560a088e64db","resolution":{"observed_at":"2026-08-11T22:56:27.022395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-11T20:10:47.422117Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.06016","last_updated":"2025-04-07T11:16:47Z","snapshot_observed_at":"2026-08-11T20:03:50.332267Z","submitted_at":"2024-12-08T18:21:00Z","title":"Track4Gen: Teaching Video Diffusion Models to Track Points Improves Video Generation","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T20:10:47.422117Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2412.06016"},"observation_digest":"sha256:952352c4f1ec027c4ba85a6a092ffcf5f5ae2a06900e89e313af276e77cac438","observation_id":"40dfe0f9-1892-4864-8d91-152c1cd58b89","resolution":{"observed_at":"2026-08-11T20:10:47.422117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-10T17:25:52.857424Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12218","last_updated":"2025-04-20T14:33:55Z","snapshot_observed_at":"2026-08-14T13:31:51.787116Z","submitted_at":"2025-01-21T15:39:40Z","title":"Exploring Temporally-Aware Features for Point Tracking","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T17:25:52.857424Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2501.12218"},"observation_digest":"sha256:ae68d6888bceaf46c15b9f5cfcca674ed1811f6a968574096498b7104f7da9d1","observation_id":"823de783-e178-4460-acb5-08ab3189a3d6","resolution":{"observed_at":"2026-08-10T17:25:52.857424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-10T17:16:52.655495Z","title":"Bootstap: Bootstrapped training for tracking-any-point","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12392","last_updated":"2025-01-21T18:59:53Z","snapshot_observed_at":"2026-08-15T15:57:50.161774Z","submitted_at":"2025-01-21T18:59:53Z","title":"Learning segmentation from point trajectories","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T17:16:52.655495Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2501.12392"},"observation_digest":"sha256:14c6ec6c2803723b5d9b4a70378180ff8e1290e744f989e362b5c657cff82876","observation_id":"4c76f0d9-cbb9-4ab1-b559-d32d3abfd1c3","resolution":{"observed_at":"2026-08-10T17:16:52.655495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":"2402.00847","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-07-04T00:59:19.505966Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":"e871da74-3c80-4569-81d7-7c47cef2c94b","year":2024},"citing_paper":{"arxiv_id":"2507.00990","last_updated":"2026-05-13T01:35:48Z","snapshot_observed_at":"2026-07-06T21:50:35.488353Z","submitted_at":"2025-07-01T17:39:59Z","title":"Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-19T06:36:13.144868Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2507.00990"},"observation_digest":"sha256:3e8b655f7af6fe63d7a2b197fb83b337514633ac94898f7814af2855db30a2fc","observation_id":"76ce2332-5b98-40f1-860f-3116ddcb1147","resolution":{"observed_at":"2026-05-19T06:37:07.329639Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-08-05T04:41:51.612220Z","title":"Boot- stap: Bootstrapped training for tracking-any-point,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.06023","last_updated":"2025-09-07T11:43:11Z","snapshot_observed_at":"2026-08-15T16:26:35.876178Z","submitted_at":"2025-09-07T11:43:11Z","title":"DVLO4D: Deep Visual-Lidar Odometry with Sparse Spatial-temporal Fusion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T04:41:51.612220Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2509.06023"},"observation_digest":"sha256:805900c91036b66db589c371a3897384c2677ad25154a8d31a7610fbf53a945e","observation_id":"7bd57a5f-7ba5-4ce8-9655-ec8aec976938","resolution":{"observed_at":"2026-08-05T04:41:51.612220Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":"2402.00847","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-07-04T00:59:19.505966Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":"e871da74-3c80-4569-81d7-7c47cef2c94b","year":2024},"citing_paper":{"arxiv_id":"2606.18558","last_updated":"2026-06-17T00:19:00Z","snapshot_observed_at":"2026-08-12T09:20:26.643022Z","submitted_at":"2026-06-17T00:19:00Z","title":"MolmoMotion: Forecasting Point Trajectories in 3D with Language Instruction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-26T21:27:47.702578Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2606.18558"},"observation_digest":"sha256:00131d481fa5505ffa0754f68d1db03c531ae111c2463beb8ce945d431b70ae9","observation_id":"aeb3cbe1-bb48-4cc0-beab-48edb0dfd092","resolution":{"observed_at":"2026-07-04T00:09:14.770606Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","version":2},"cited_work":{"arxiv_id":"2402.00847","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.00847","snapshot_observed_at":"2026-07-04T00:59:19.505966Z","title":"Bootstap: Boot- strapped training for tracking-any-point","venue":null,"work_id":"e871da74-3c80-4569-81d7-7c47cef2c94b","year":2024},"citing_paper":{"arxiv_id":"2606.19333","last_updated":"2026-06-17T17:57:34Z","snapshot_observed_at":"2026-08-12T21:11:47.095223Z","submitted_at":"2026-06-17T17:57:34Z","title":"Do as I Do: Dexterous Manipulation Data from Everyday Human Videos","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-06-26T20:51:21.209882Z"},"links":{"cited_paper":"/paper/2402.00847","citing_paper":"/paper/2606.19333"},"observation_digest":"sha256:696f915081647eee313e36f4f586c815fc5b4c308a0ef80a5d7e27855914b55e","observation_id":"e5f5c4cf-0253-4ef2-907a-85e91a52f03b","resolution":{"observed_at":"2026-07-04T00:59:19.510279Z","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/2402.00847/citation-record","integrity":"/paper/2402.00847/integrity","json":"/paper/2402.00847/citation-record.json","paper":"/paper/2402.00847"},"outbound":[],"paper":{"arxiv_id":"2402.00847","last_updated":"2024-05-23T15:00:26Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T19:20:49.291123Z","submitted_at":"2024-02-01T18:38:55Z","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point"},"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 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2402.00847."}