{"as_of":"2026-08-18T03:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9dc5f957c3b40b4710e4e3df648f912fc2855f10116e2f34b8db61471fde00a7","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":"2026-08-17T06:30:58.91139+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":"2026-08-12T13:10:26.618471Z","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":"2026-08-07T14:34:05.395202Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.15845","last_updated":"2024-07-22T17:59:10Z","snapshot_observed_at":"2026-08-16T13:32:02.995189Z","submitted_at":"2024-07-22T17:59:10Z","title":"Reconstructing Training Data From Real World Models Trained with Transfer Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15845","snapshot_observed_at":"2026-08-12T13:10:26.618471Z","title":"Reconstructing training data from real world models trained with transfer learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16458","last_updated":"2024-11-25T15:05:00Z","snapshot_observed_at":"2026-08-12T13:03:19.524829Z","submitted_at":"2024-11-25T15:05:00Z","title":"On the Reconstruction of Training Data from Group Invariant Networks","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-12T13:10:26.618471Z"},"links":{"cited_paper":"/paper/2407.15845","citing_paper":"/paper/2411.16458"},"observation_digest":"sha256:e647ea5019be8720643681dd5a62cb75fdd78d9470a00fb5996b14dced5d96d0","observation_id":"10c2c274-a524-4ac5-a3be-c1429f4effe8","resolution":{"observed_at":"2026-08-12T13:10:26.618471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15845","last_updated":"2024-07-22T17:59:10Z","snapshot_observed_at":"2026-08-16T13:32:02.995189Z","submitted_at":"2024-07-22T17:59:10Z","title":"Reconstructing Training Data From Real World Models Trained with Transfer Learning","version":1},"cited_work":{"arxiv_id":"2407.15845","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.15845","snapshot_observed_at":"2026-08-07T14:34:05.395202Z","title":"Reconstructing Training Data From Real World Models Trained with Transfer Learning","venue":"cs.LG","work_id":"3609b7a4-777a-4ec9-a828-ec10ed63b012","year":2024},"citing_paper":{"arxiv_id":"2505.19019","last_updated":"2025-05-25T07:53:03Z","snapshot_observed_at":"2026-08-14T08:25:38.524402Z","submitted_at":"2025-05-25T07:53:03Z","title":"Querying Kernel Methods Suffices for Reconstructing their Training Data","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T14:34:03.629910Z"},"links":{"cited_paper":"/paper/2407.15845","citing_paper":"/paper/2505.19019"},"observation_digest":"sha256:7bbc76d323fcd82592f3bdade16fb525e1f2520162fab50fcdad64377a7f119f","observation_id":"bf8d34c5-7265-4004-b4a5-e3d2e333fce4","resolution":{"observed_at":"2026-08-07T14:34:05.491036Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.15845/citation-record","integrity":"/paper/2407.15845/integrity","json":"/paper/2407.15845/citation-record.json","paper":"/paper/2407.15845"},"outbound":[],"paper":{"arxiv_id":"2407.15845","last_updated":"2024-07-22T17:59:10Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T13:32:02.995189Z","submitted_at":"2024-07-22T17:59:10Z","title":"Reconstructing Training Data From Real World Models Trained with Transfer Learning"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.15845."}