{"as_of":"2026-08-08T05:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:28c170b926106e69a0e851d6a0eabf5e71acb8237b16f114ff8da41b4252235d","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":"2026-08-07T06:34:17.273281+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":"2026-08-06T20:02:08.850086Z","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":"2026-05-15T14:15:55.524415Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.10468","last_updated":"2024-09-05T15:47:45Z","snapshot_observed_at":"2026-08-07T22:51:48.145160Z","submitted_at":"2024-08-20T00:40:49Z","title":"Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.10468","snapshot_observed_at":"2026-08-06T20:02:08.850086Z","title":"Tracing privacy leakage of language models to training data via adjusted influence functions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04059","last_updated":"2025-07-05T14:46:42Z","snapshot_observed_at":"2026-08-07T12:31:08.588633Z","submitted_at":"2025-07-05T14:46:42Z","title":"Attributing Data for Sharpness-Aware Minimization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:02:08.850086Z"},"links":{"cited_paper":"/paper/2408.10468","citing_paper":"/paper/2507.04059"},"observation_digest":"sha256:c129168cd030e4c7362afaf2e3ddd8480eb3f9b481ba95cc850f09fd6f447a6d","observation_id":"11560f73-d871-4cce-99cf-ac5ce6f6818a","resolution":{"observed_at":"2026-08-06T20:02:08.850086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.10468","last_updated":"2024-09-05T15:47:45Z","snapshot_observed_at":"2026-08-07T22:51:48.145160Z","submitted_at":"2024-08-20T00:40:49Z","title":"Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions","version":4},"cited_work":{"arxiv_id":"2408.10468","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.10468","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tracing privacy leakage of language models to training data via adjusted influence functions","venue":null,"work_id":"9dd34376-b5eb-4ab7-bb1d-2b4e3e73c946","year":2024},"citing_paper":{"arxiv_id":"2603.09002","last_updated":"2026-04-26T14:13:48Z","snapshot_observed_at":"2026-07-06T22:48:26.306802Z","submitted_at":"2026-03-09T22:46:27Z","title":"Security Considerations for Multi-agent Systems","version":2},"reference_index":251,"source":"pdf_text","source_observed_at":"2026-05-15T14:12:14.160789Z"},"links":{"cited_paper":"/paper/2408.10468","citing_paper":"/paper/2603.09002"},"observation_digest":"sha256:2e3c53060a9941e51b8e7815bd60039367158d8ffdb6c41c7566609c448deafb","observation_id":"1283f191-a502-4323-93ba-818d54495506","resolution":{"observed_at":"2026-05-15T14:15:55.527062Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2408.10468/citation-record","integrity":"/paper/2408.10468/integrity","json":"/paper/2408.10468/citation-record.json","paper":"/paper/2408.10468"},"outbound":[],"paper":{"arxiv_id":"2408.10468","last_updated":"2024-09-05T15:47:45Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T22:51:48.145160Z","submitted_at":"2024-08-20T00:40:49Z","title":"Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions"},"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 2 inbound Pith citation observations for arXiv:2408.10468."}