{"as_of":"2026-08-17T04:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5621cb93815b7a6306e1cf13fd243c547164ea29426d82d82f34f1ea6a8c95e2","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T21:28:13.536130Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T10:37:53.084576Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.08711","last_updated":"2024-07-11T17:49:05Z","snapshot_observed_at":"2026-08-16T13:34:59.442799Z","submitted_at":"2024-07-11T17:49:05Z","title":"OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objects","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08711","snapshot_observed_at":"2026-08-11T21:28:13.536130Z","title":"Omninocs: A unified nocs dataset and model for 3d lifting of 2d objects","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.04458","last_updated":"2024-12-05T18:59:09Z","snapshot_observed_at":"2026-08-14T20:09:22.418658Z","submitted_at":"2024-12-05T18:59:09Z","title":"Cubify Anything: Scaling Indoor 3D Object Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T21:28:13.536130Z"},"links":{"cited_paper":"/paper/2407.08711","citing_paper":"/paper/2412.04458"},"observation_digest":"sha256:efeb483769e559057c16d17b8e7c248eeef7982b6aed5180d9cfc32bc38456b6","observation_id":"41a6ee58-f24c-489d-8bef-c08ac7a93521","resolution":{"observed_at":"2026-08-11T21:28:13.536130Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08711","last_updated":"2024-07-11T17:49:05Z","snapshot_observed_at":"2026-08-16T13:34:59.442799Z","submitted_at":"2024-07-11T17:49:05Z","title":"OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objects","version":1},"cited_work":{"arxiv_id":"2407.08711","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.08711","snapshot_observed_at":"2026-08-05T10:37:53.084576Z","title":"OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objects","venue":"cs.CV","work_id":"1af2d9cf-0062-4d6a-b9c3-5b8dd93eadde","year":2024},"citing_paper":{"arxiv_id":"2509.03893","last_updated":"2025-09-04T05:39:16Z","snapshot_observed_at":"2026-08-12T19:08:47.124978Z","submitted_at":"2025-09-04T05:39:16Z","title":"Weakly-Supervised Learning of Dense Functional Correspondences","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T10:37:52.465978Z"},"links":{"cited_paper":"/paper/2407.08711","citing_paper":"/paper/2509.03893"},"observation_digest":"sha256:542d9823b106c3468d7af33670fd1ae19e8d98b5679744418e936c53b8bc7710","observation_id":"ac6f7933-b605-49a4-809e-6dbe25049322","resolution":{"observed_at":"2026-08-05T10:37:53.089894Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.08711/citation-record","integrity":"/paper/2407.08711/integrity","json":"/paper/2407.08711/citation-record.json","paper":"/paper/2407.08711"},"outbound":[],"paper":{"arxiv_id":"2407.08711","last_updated":"2024-07-11T17:49:05Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T13:34:59.442799Z","submitted_at":"2024-07-11T17:49:05Z","title":"OmniNOCS: A unified NOCS dataset and model for 3D lifting of 2D objects"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.08711."}