{"as_of":"2026-08-10T00:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4656e6143ce6389a1cadf179e3f5c675e7456a7bee5c7da816c40cb5eb9f5352","coverage":[{"denominator":26,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":26,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T06:01:02.143482Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2604.23795/citation-record","integrity":"/paper/2604.23795/integrity","json":"/paper/2604.23795/citation-record.json","paper":"/paper/2604.23795"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"An investigation of data privacy and utility using machine learning as a gauge","venue":null,"work_id":"7262f09f-fd8c-4895-96c2-f5e97b8f3f43","year":2014},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:62c440ff54c60be566283fad11e8dbb24b5aa609e605c28f66f2d62e45c18372","observation_id":"593a3f77-e82d-4040-8f1a-cd4207a7fb3b","resolution":{"observed_at":"2026-05-26T19:18:14.719923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"1309.3958","last_updated":"2013-09-16T13:47:59Z","snapshot_observed_at":"2026-08-05T17:19:02.288909Z","submitted_at":"2013-09-16T13:47:59Z","title":"Utilizing Noise Addition for Data Privacy, an Overview","version":1},"cited_work":{"arxiv_id":"1309.3958","doi":"10.48550/arxiv.1309.3958","metadata_source":"arxiv_reference","pith_arxiv_id":"1309.3958","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Utilizing noise addition for data privacy, an overview","venue":"arXiv (Cornell University)","work_id":"246d852c-4091-4637-940f-f636f55fd964","year":2013},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"cited_paper":"/paper/1309.3958","citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:d693816ed5124239f7ac79eac893221071385c0c6e69cc9aa8bbc2e4ad05f39f","observation_id":"490cce1e-c33f-4195-986c-0483a0996b17","resolution":{"observed_at":"2026-07-04T18:39:31.048910Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep learning with differential privacy","venue":null,"work_id":"40d7e8d3-e6f6-4dde-a002-e0f98ca7072b","year":2016},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:d12a5504605d0d7c6fb0606b51e3ad2cd390c2d3dd6b6ca48f23e2222aa2a1ee","observation_id":"16de756d-e90c-48bd-9a65-7984070bc25a","resolution":{"observed_at":"2026-05-26T19:18:14.707415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Differential privacy","venue":null,"work_id":"20b6d2d3-3b0f-4c33-a582-e2985765c0b6","year":2006},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:d5ec46802750d33df9e2f0dc8d178a408596eef383af2b58a88f1ed6cb8f6ee1","observation_id":"0666d167-8b28-4735-bfb8-47ce203f6728","resolution":{"observed_at":"2026-05-26T19:18:14.675844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Membership inference attacks against machine learning models","venue":null,"work_id":"b320bc14-75ce-4a72-b7dd-0f799f4ef862","year":2017},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:a4ce3b3b360715af22ccedda21b98e3e948167a60fb9286fcbb8115bd933abb5","observation_id":"d94b77b4-e411-4d4e-83c0-146ccb7c8222","resolution":{"observed_at":"2026-05-26T19:18:14.709362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Privacy risk in machine learning: Analyz- ing the connection to overfitting","venue":null,"work_id":"8bcf3856-2eb6-422a-b802-4365623d1d05","year":2018},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:dc8f42089b41107f4f0c4ec12b874c8092ccc7db2a8cd80c7ae40215e5f3f0c5","observation_id":"92c879ea-4d39-46b3-9642-e3b63b63e1c6","resolution":{"observed_at":"2026-05-26T19:18:14.700335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Private empirical risk minimization","venue":null,"work_id":"713cd867-b576-4bc7-ae95-50e7289d2ef8","year":2016},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:d82b67441dd221a2a417e3ce91f51af7c98b75d4a4f1cefbb6c58e7cc886d37d","observation_id":"e48939c1-5039-4ba1-8856-7b879c6816ea","resolution":{"observed_at":"2026-05-26T19:18:14.686176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Private stochastic convex optimization: Optimal rates inℓ 1 geom- etry","venue":null,"work_id":"1ce8992a-22c5-4feb-96a4-65277f14a6fc","year":2020},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:167c44495cf9f695934a4b0fc982e6a822dc98f21e5459f475e1953ddbc8262a","observation_id":"5abf7bc0-7025-4d82-8426-66c2238839ac","resolution":{"observed_at":"2026-05-26T19:18:14.711023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"EW-Tune: A framework for privately fine-tuning large language models with differential privacy","venue":null,"work_id":"9492c154-e874-4407-a32f-5509389b9cd1","year":2022},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:845748f8fd5d51841cd61ed6ba806430de2bf58dba055049353a41ec801a6a27","observation_id":"12bac186-a97c-4946-a6bc-d1440f6a8e15","resolution":{"observed_at":"2026-05-26T19:18:14.689446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"PrivLLM-Guard: An adaptive differential privacy framework for clinical large language models","venue":null,"work_id":"c958f858-c8fb-43cd-a868-d2def722594c","year":2026},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:f78c4795ecc077f8470354bb612f78ee3ba2ab6465bc863c2fb1a0f8d2759f03","observation_id":"51e70973-ae0c-4036-b039-93c1c8703227","resolution":{"observed_at":"2026-05-26T19:18:14.678668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enhancing large lan- guage model privacy with differentially private parameter-efficient fine-tuning","venue":null,"work_id":"600a90a2-c226-43fb-9d9c-bf52cccd04c3","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:344a466149a1348ec009466f35a91477efb7e0c9745278f8562c2cc9fc57549e","observation_id":"48c8cf86-a618-4eba-b6b1-b2513bd13b68","resolution":{"observed_at":"2026-05-26T19:18:14.716566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Differential privacy in the era of large- scale generative AI","venue":null,"work_id":"4d2fa01b-0ec8-4adb-9d41-78a9d43f5e3a","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:effa2500da30c7d7f1ebdbaaa2a86b16068a45d7101589fd11f26b86f1ab5871","observation_id":"4e5f99e4-f2c3-464a-adb7-455a0ede5b84","resolution":{"observed_at":"2026-05-26T19:18:14.650006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Leveraging open LLMs for pri- vate adaptation without exposing data","venue":null,"work_id":"3aac109b-ea47-4eba-88d9-a9001d5f0633","year":2024},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:b234e9a030357b5caaf1558194edebe82c189b5c755869b4016471c25e0f1c72","observation_id":"90540578-9622-416c-9eb3-78713fc3428d","resolution":{"observed_at":"2026-05-26T19:18:14.681885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Privacy-Flat: Towards flatter loss landscape for privacy-preserving large lan- guage models","venue":null,"work_id":"07aa8a99-4f91-403c-a359-ddc971f0b890","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:48066b53698de736e2c40452b5d2516bdf6811489bcac027763ff197181a423a","observation_id":"7b6a1aee-9bd9-4063-a60b-3527ff1dc315","resolution":{"observed_at":"2026-05-26T19:18:14.696763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2310.10383","last_updated":"2024-09-30T11:58:27Z","snapshot_observed_at":"2026-08-03T23:12:05.533433Z","submitted_at":"2023-10-16T13:23:54Z","title":"Privacy in Large Language Models: Attacks, Defenses and Future Directions","version":2},"cited_work":{"arxiv_id":"2310.10383","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10383","snapshot_observed_at":"2026-07-04T14:59:54.879675Z","title":"Privacy in large language models: Attacks, defenses and future directions","venue":null,"work_id":"2613543e-71bb-416d-82e8-9c4eac8949b1","year":2018},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"cited_paper":"/paper/2310.10383","citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:28354076c38fb8a10de5fc656ad8de6ccbba38f4f18cce169678ac6a4576721d","observation_id":"4578cf47-3ca1-496c-a0b8-937c53900a16","resolution":{"observed_at":"2026-05-11T21:16:33.235994Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Privacy-Preserving4LLM: A benchmark for privacy-preserving techniques in large lan- guage model training","venue":null,"work_id":"20eaeae2-b164-48ff-8426-cb08a6b2af52","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:14efe4d5dea2429b26e360946e5f71b2e39550a3563af4caae2ba1000ae0bb65","observation_id":"99434425-913d-4c2f-82c8-3cd97c5cb6dc","resolution":{"observed_at":"2026-05-26T19:18:14.717901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large language models are privacy-erasable","venue":null,"work_id":"96e20ff6-ca5c-48a2-880e-dee05e477683","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:ddbf3aaeec8240b37d459082dad5489053585e615bdaf4fdbbaad79224997b3a","observation_id":"ba50d928-087d-4a52-b4cd-bc413ecbb623","resolution":{"observed_at":"2026-05-26T19:18:14.695434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Towards a human-centered LLM privacy research agenda","venue":null,"work_id":"0e3bb22a-16a9-44d3-9d1d-33fe4b4d99ae","year":2024},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:bd403f8817c3d89747a06c6ec5467dfb56a3b5bdb015ed4efd8edacfc8fc8fa9","observation_id":"51c77b10-e690-445d-aca4-487b84d8710f","resolution":{"observed_at":"2026-05-26T19:18:14.706046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Human-centred privacy audits for large language models","venue":null,"work_id":"886450c3-58f2-4c24-a77a-94f02b60c60e","year":2026},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:dface36279ee17a74c488d52bfe61c4b5e944cc052919c1ed369bf0181e4b8d5","observation_id":"da43b7c0-19e4-4148-8501-455d2a7cc0b0","resolution":{"observed_at":"2026-05-26T19:18:14.727636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Human-centered privacy framework for AI systems","venue":null,"work_id":"c42d6b41-7342-4c48-8eea-eaf91162f283","year":2026},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:b54641c33662855203d3463a4f3db5ac0106cda38e92e76aea04ab3b395a99f2","observation_id":"5dfa0311-b29c-4328-9de1-de7e9b8e6c2f","resolution":{"observed_at":"2026-05-26T19:18:14.685604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Human- centric AI: Philosophical foundations","venue":null,"work_id":"96467e2f-3cde-4ca8-b8ef-c9ff49b6c4cb","year":2024},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:2f1dfad0a86fe1aa228869d8e6ff9c25bc57a54ac91b4ed7a9c7efce51f9450d","observation_id":"e2a36763-e0c9-49e6-a720-6665d980a4fd","resolution":{"observed_at":"2026-05-26T19:18:14.723711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Security and privacy challenges of large language models","venue":null,"work_id":"320ed060-d762-46e7-8e7b-82e84d83a8d8","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:75dfe6d5bc1dec38f8dfba23f31769e26cdc8c55356a0d2582d8f5976933482e","observation_id":"b3b30824-7c3b-45b7-834d-9e227e33ce89","resolution":{"observed_at":"2026-05-26T19:18:14.702909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DP-RAG: Applying differen- tial privacy to retrieval-augmented generation","venue":null,"work_id":"fb238b40-2958-42c9-a207-b3e0708e55b6","year":2025},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:4481bf390646f8d3f325b06d3989f17d6a781d529dc4c6bc4f7261f98f69f9ed","observation_id":"8de7519e-6eea-4b08-a88c-a68fa34a9aea","resolution":{"observed_at":"2026-05-26T19:18:14.721193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Extracting training data from large language models","venue":null,"work_id":"36ca0227-6dad-418a-8e11-02f72f486a7f","year":2021},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:5fcc527c6c2e62dfc39fb6c9c72e5a9ef98035c298c75d0e7ad4fced4bd08a92","observation_id":"133c1453-4245-48a7-8365-ac6f7ab6fb21","resolution":{"observed_at":"2026-05-26T19:18:14.692794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"EU Artificial Intelli- gence Act","venue":null,"work_id":"f60cf6b0-90f0-405a-a414-94b7175a31be","year":2024},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:88a1dd6dba9fb9d28d07197b73fc384753ea55f53d481f994029253fd3825873","observation_id":"99b462e9-fc5d-4385-95d8-9674a553f364","resolution":{"observed_at":"2026-05-26T19:18:14.712373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"AI Risk Management Framework","venue":null,"work_id":"a16093d2-f095-43ee-b12b-4a1ff1219e4b","year":2023},"citing_paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T06:01:02.143482Z"},"links":{"citing_paper":"/paper/2604.23795"},"observation_digest":"sha256:1255b7a9c1d5f26820f8c2ddcb26ffc1733d2e2e47df8c1bd88b7441652fb407","observation_id":"4a6856e0-2d34-4295-9f2d-6c4280ed5809","resolution":{"observed_at":"2026-05-26T19:18:14.714352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"2604.23795","last_updated":"2026-04-26T16:39:37Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-02T08:05:42.990771Z","submitted_at":"2026-04-26T16:39:37Z","title":"LLM-CEG: Extending the Classification Error Gauge Framework for Privacy Auditing of Large Language Models"},"reference_resolution":{"displayed":26,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":24},"total_outbound_references":26},"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 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2604.23795."}