{"as_of":"2026-08-09T15:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c272e8eef6729705b3cb031adf2cb671618bfa12a6ab77be37012aca3f39588e","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:49:44.766456Z","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":"2026-07-03T17:38:43.800061Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2305.16157","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-07-03T17:38:43.800061Z","title":"Training data extraction from pre-trained language models: A survey","venue":null,"work_id":"a8f3dcbc-c82d-4532-8351-1cef3e8d4df2","year":2023},"citing_paper":{"arxiv_id":"2402.16391","last_updated":"2026-04-28T07:39:39Z","snapshot_observed_at":"2026-08-01T03:48:12.462157Z","submitted_at":"2024-02-26T08:31:45Z","title":"Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions","version":4},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-24T04:21:49.775278Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2402.16391"},"observation_digest":"sha256:3abed8eba32203a9a8c382d220887af0b863028f62d714b9ba0417a73f774a9c","observation_id":"499c5ad2-eac6-46c7-a8cd-ec02c99ac667","resolution":{"observed_at":"2026-05-24T04:23:52.833925Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-08-07T13:49:44.766456Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20910","last_updated":"2025-08-08T10:06:38Z","snapshot_observed_at":"2026-08-09T01:59:15.505354Z","submitted_at":"2025-05-27T09:00:12Z","title":"Automated Privacy Information Annotation in Large Language Model Interactions","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:49:44.766456Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2505.20910"},"observation_digest":"sha256:8123d9b516e5a8659182316d5d9c44c7016707efe64dfbfba203ade5de1f4714","observation_id":"6cd58c6c-a051-4c8e-990b-229f98191f18","resolution":{"observed_at":"2026-08-07T13:49:44.766456Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2305.16157","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-07-03T17:38:43.800061Z","title":"Training data extraction from pre-trained language models: A survey","venue":null,"work_id":"a8f3dcbc-c82d-4532-8351-1cef3e8d4df2","year":2023},"citing_paper":{"arxiv_id":"2605.05224","last_updated":"2026-04-18T11:00:56Z","snapshot_observed_at":"2026-08-02T18:12:50.004030Z","submitted_at":"2026-04-18T11:00:56Z","title":"Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T07:07:13.072332Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2605.05224"},"observation_digest":"sha256:89bf3b453de8fb315c6fb31eb62f78f7a83d09dcdfc4adc719630eb8d41c107c","observation_id":"aed2183e-791d-42a1-ad2e-b30a1bb9c7fc","resolution":{"observed_at":"2026-05-10T07:11:53.515645Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2305.16157","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-07-03T17:38:43.800061Z","title":"Training data extraction from pre-trained language models: A survey","venue":null,"work_id":"a8f3dcbc-c82d-4532-8351-1cef3e8d4df2","year":2023},"citing_paper":{"arxiv_id":"2605.26133","last_updated":"2026-05-21T10:32:33Z","snapshot_observed_at":"2026-08-07T10:44:40.983544Z","submitted_at":"2026-05-21T10:32:33Z","title":"Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T17:20:16.735285Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2605.26133"},"observation_digest":"sha256:3c7f94641e8dc98065cc3ac23abd5532a9e9f6f070db590274869fc6522a7a7c","observation_id":"29d0ca2e-9c6f-49d9-8fac-b63c346a5dc6","resolution":{"observed_at":"2026-06-30T17:24:57.276447Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2305.16157","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-07-03T17:38:43.800061Z","title":"Training data extraction from pre-trained language models: A survey","venue":null,"work_id":"a8f3dcbc-c82d-4532-8351-1cef3e8d4df2","year":2023},"citing_paper":{"arxiv_id":"2606.03399","last_updated":"2026-06-02T09:40:56Z","snapshot_observed_at":"2026-08-05T05:02:37.466675Z","submitted_at":"2026-06-02T09:40:56Z","title":"Selective Token-Level Cryptographic Redaction for Privacy-Preserving Clinical Deployment of Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T10:19:20.891082Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2606.03399"},"observation_digest":"sha256:3133d0e7aea5cb3e0305279da57c3fac2f02b600d38d7cc18d96392fe49afb9a","observation_id":"2ec034f5-e745-4cee-8f61-6c76139dabe1","resolution":{"observed_at":"2026-07-02T03:06:30.144763Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2305.16157","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.16157","snapshot_observed_at":"2026-07-03T17:38:43.800061Z","title":"Training data extraction from pre-trained language models: A survey","venue":null,"work_id":"a8f3dcbc-c82d-4532-8351-1cef3e8d4df2","year":2023},"citing_paper":{"arxiv_id":"2606.17110","last_updated":"2026-06-15T07:04:01Z","snapshot_observed_at":"2026-08-05T23:11:05.452983Z","submitted_at":"2026-06-15T07:04:01Z","title":"Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T03:59:30.468854Z"},"links":{"cited_paper":"/paper/2305.16157","citing_paper":"/paper/2606.17110"},"observation_digest":"sha256:debf96926da192f241742c56e8aa41859921d813dc46afeeae659eefcb9eaa52","observation_id":"b5d84111-d3a6-4d90-823a-f55f6aff2fb6","resolution":{"observed_at":"2026-07-03T17:38:43.801565Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.16157/citation-record","integrity":"/paper/2305.16157/integrity","json":"/paper/2305.16157/citation-record.json","paper":"/paper/2305.16157"},"outbound":[],"paper":{"arxiv_id":"2305.16157","last_updated":"2023-05-25T15:23:29Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T15:33:23.984280Z","submitted_at":"2023-05-25T15:23:29Z","title":"Training Data Extraction From Pre-trained Language Models: A Survey"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.16157."}