{"as_of":"2026-08-05T21:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:36873fbc1fa6a8a56abff63909da0eadc2815888aa85e3b67bfbe20aaf4ad93c","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-01T05:07:58.441326Z","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":"2026-07-01T10:45:42.798457Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.14367","last_updated":"2024-01-25T18:14:57Z","snapshot_observed_at":"2026-07-06T17:20:33.356092Z","submitted_at":"2024-01-25T18:14:57Z","title":"Genie: Achieving Human Parity in Content-Grounded Datasets Generation","version":1},"cited_work":{"arxiv_id":"2401.14367","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.14367","snapshot_observed_at":"2026-07-01T10:45:42.798457Z","title":"Yehudai, B","venue":null,"work_id":"ec60ddd8-ca2f-475d-a77d-7b0f30ae8b66","year":2024},"citing_paper":{"arxiv_id":"2406.11354","last_updated":"2026-04-23T15:54:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-17T09:17:40Z","title":"Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression","version":3},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-05-24T00:09:52.093810Z"},"links":{"cited_paper":"/paper/2401.14367","citing_paper":"/paper/2406.11354"},"observation_digest":"sha256:d18f7763d334cd7b2eeb4e4339f2e0122b6eff3643b1920334c6d9147cb23c61","observation_id":"adbcc86a-b692-4d58-a903-75539cbaa64b","resolution":{"observed_at":"2026-05-24T00:13:39.642141Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14367","last_updated":"2024-01-25T18:14:57Z","snapshot_observed_at":"2026-07-06T17:20:33.356092Z","submitted_at":"2024-01-25T18:14:57Z","title":"Genie: Achieving Human Parity in Content-Grounded Datasets Generation","version":1},"cited_work":{"arxiv_id":"2401.14367","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.14367","snapshot_observed_at":"2026-07-01T10:45:42.798457Z","title":"Yehudai, B","venue":null,"work_id":"ec60ddd8-ca2f-475d-a77d-7b0f30ae8b66","year":2024},"citing_paper":{"arxiv_id":"2604.23054","last_updated":"2026-04-24T22:48:10Z","snapshot_observed_at":"2026-07-06T23:09:19.041332Z","submitted_at":"2026-04-24T22:48:10Z","title":"DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T11:31:50.819449Z"},"links":{"cited_paper":"/paper/2401.14367","citing_paper":"/paper/2604.23054"},"observation_digest":"sha256:37ee95a6e7a37dc96bad9569095b96533ea345c5d68bcc901bb69160877df0d5","observation_id":"2d059fd2-4757-463d-8be9-510abfa4e09a","resolution":{"observed_at":"2026-05-11T19:36:13.945606Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14367","last_updated":"2024-01-25T18:14:57Z","snapshot_observed_at":"2026-07-06T17:20:33.356092Z","submitted_at":"2024-01-25T18:14:57Z","title":"Genie: Achieving Human Parity in Content-Grounded Datasets Generation","version":1},"cited_work":{"arxiv_id":"2401.14367","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.14367","snapshot_observed_at":"2026-07-01T10:45:42.798457Z","title":"Yehudai, B","venue":null,"work_id":"ec60ddd8-ca2f-475d-a77d-7b0f30ae8b66","year":2024},"citing_paper":{"arxiv_id":"2606.32002","last_updated":"2026-06-30T17:35:14Z","snapshot_observed_at":"2026-08-02T13:47:40.317163Z","submitted_at":"2026-06-30T17:35:14Z","title":"Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-01T05:07:58.441326Z"},"links":{"cited_paper":"/paper/2401.14367","citing_paper":"/paper/2606.32002"},"observation_digest":"sha256:88305c828a775c3cee2b0b380e62337083c5dd101874e146ebdc3ec30f66ff72","observation_id":"3a6a502a-79f0-4ba1-9ebf-d271c3857d61","resolution":{"observed_at":"2026-07-01T10:45:42.800093Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2401.14367/citation-record","integrity":"/paper/2401.14367/integrity","json":"/paper/2401.14367/citation-record.json","paper":"/paper/2401.14367"},"outbound":[],"paper":{"arxiv_id":"2401.14367","last_updated":"2024-01-25T18:14:57Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:20:33.356092Z","submitted_at":"2024-01-25T18:14:57Z","title":"Genie: Achieving Human Parity in Content-Grounded Datasets Generation"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.14367."}