{"as_of":"2026-08-23T15:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b9715a8204ba7e7d6038eed615cd8112558035b3341e1449c8497b1b166f9ce3","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T22:53:25.649814Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2505.06027/citation-record","integrity":"/paper/2505.06027/integrity","json":"/paper/2505.06027/citation-record.json","paper":"/paper/2505.06027"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-15T22:53:24.713875Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.713875Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:79a10e641ddb500bf31cd47dd086c7c8287db6a68509810eef22a66dc9079aa5","observation_id":"8b2cadc2-a9b6-4bc6-a2bf-5db55de6f300","resolution":{"observed_at":"2026-08-15T22:53:24.713875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:24.776205Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.776205Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:1be24a2463660549f990780f0c117cbc07340b1fef1f3ea187e51ced87c011f1","observation_id":"4e5230ff-251f-405d-9c1b-88461b41446e","resolution":{"observed_at":"2026-08-15T22:53:24.776205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.979987Z","title":null,"venue":null,"work_id":"168557e1-c59d-4b3f-9ddf-b29cb1353583","year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.781416Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:8c6269dc50e0bbf0271a1c0ac03da7858d821216e5974fb1284cac719e1c1f65","observation_id":"d4677326-ffe3-4602-a7ea-4a1428cb4989","resolution":{"observed_at":"2026-08-15T22:53:27.027488Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.00383","last_updated":"2025-04-18T06:58:12Z","snapshot_observed_at":"2026-08-17T07:44:33.848682Z","submitted_at":"2024-11-30T07:21:02Z","title":"Unified Parameter-Efficient Unlearning for LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.00383","snapshot_observed_at":"2026-08-15T22:53:24.785424Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.785424Z"},"links":{"cited_paper":"/paper/2412.00383","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:6e6918ad12b4305e48cba2e63e72ebc4a84254e58ed4c982458f61c9dca9165c","observation_id":"e84d8b2e-b64f-4f97-9780-c5772e64f029","resolution":{"observed_at":"2026-08-15T22:53:24.785424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10052","last_updated":"2024-10-16T11:50:27Z","snapshot_observed_at":"2026-08-18T12:35:25.936578Z","submitted_at":"2024-02-15T16:21:14Z","title":"UNDIAL: Self-Distillation with Adjusted Logits for Robust Unlearning in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.10052","snapshot_observed_at":"2026-08-15T22:53:24.789754Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.789754Z"},"links":{"cited_paper":"/paper/2402.10052","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:87d2b56fc4bad27fc28e050296977a2718d7e985bdfef72e944c99341614e552","observation_id":"7f14e367-0b0a-4c46-a46b-3286abdf91ab","resolution":{"observed_at":"2026-08-15T22:53:24.789754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-15T22:53:24.812727Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.812727Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:33d36e9491e3eb0cb3bc1602a052d31e56c47b586ea5762bf4aa3e3ca5f86b77","observation_id":"62f9ded0-b23e-4f8b-a946-d2fbf9e3e13f","resolution":{"observed_at":"2026-08-15T22:53:24.812727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:24.913723Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.913723Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:801cec80e8aa5df564933fe9f69ebb0195fd9890aed4a1f59472e675fc489e1c","observation_id":"24dcbc04-8a1f-42c0-8b46-166ab501f2b7","resolution":{"observed_at":"2026-08-15T22:53:24.913723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02238","last_updated":"2023-10-04T05:20:19Z","snapshot_observed_at":"2026-08-18T10:13:38.925008Z","submitted_at":"2023-10-03T17:48:14Z","title":"Who's Harry Potter? Approximate Unlearning in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02238","snapshot_observed_at":"2026-08-15T22:53:24.917616Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.917616Z"},"links":{"cited_paper":"/paper/2310.02238","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:74a4712cbcc680d8c3cbe8f145fb702924e1bb6d164ed4646754b4bfa77a18d3","observation_id":"93880fec-b7f2-4cfd-bd81-b7df32da4e27","resolution":{"observed_at":"2026-08-15T22:53:24.917616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:24.921727Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.921727Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:fea7a8df5e687384e053d4477764c55c082829c0e311ecc90ed3d684c2f6c976","observation_id":"4ec74ce1-6973-4503-ab28-c3791bf7a223","resolution":{"observed_at":"2026-08-15T22:53:24.921727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.961371Z","title":null,"venue":null,"work_id":"4b2f19ac-5f85-4084-a0a6-d23bd79662b1","year":2016},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.925773Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:b92a576ca6bf322566e7051cce8659e598b0345ac6b4269e038e64509e6348cf","observation_id":"e729bf83-e193-4462-b961-fc6a100aa815","resolution":{"observed_at":"2026-08-15T22:53:26.965387Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-15T22:53:24.929706Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.929706Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:ccc7623cbb488cb75b8e14ddc11b5cc906078f041d94d882901500b2d26a65eb","observation_id":"28a4188a-813f-450d-99e8-14935687fac1","resolution":{"observed_at":"2026-08-15T22:53:24.929706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.826523Z","title":null,"venue":null,"work_id":"2762ca3c-0f84-40a3-869b-e73f0f43465a","year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.935084Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:ff338d198eaa4c88c10a3ac1ca497b37d280225b43e9756ef4532bfb2e4f38d7","observation_id":"3fff1824-aee7-4c0e-a9e1-8ca661a3fcef","resolution":{"observed_at":"2026-08-15T22:53:26.899604Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2405.15495","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.041023Z","title":null,"venue":null,"work_id":"375d89db-0ae3-4f48-8e61-f6397aca1197","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.939396Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:6ac6a29b65faeffe7debe854e5462d16d6e8af5b6e7a73303d4056318b4736e8","observation_id":"bcdcee7a-d17c-46a9-a34e-b84276284cb3","resolution":{"observed_at":"2026-08-15T22:53:26.073184Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:24.943468Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.943468Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:2598f15e342a69bef9bc1aae12d0cf7b7c745356df27defbd1ddc8aedc0dd386","observation_id":"aecec13f-5efd-4b60-920c-ecb6bafc4edd","resolution":{"observed_at":"2026-08-15T22:53:24.943468Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-08-16T18:00:58.008096Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-15T22:53:24.947275Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.947275Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:17087b6ced3ee9c665371bb84d87f0d6b731c42330f2d91d0a11c950e1cec1f3","observation_id":"17047859-2edc-430f-8201-465dd21e9800","resolution":{"observed_at":"2026-08-15T22:53:24.947275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:24.961127Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:24.961127Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:f798cd34772f4bc6893d2cd30872d130dc1729ab038460d727fbeb92fe328e57","observation_id":"a4c48011-d4d3-44ad-9da7-f248d1a487aa","resolution":{"observed_at":"2026-08-15T22:53:24.961127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10890","last_updated":"2024-06-16T10:47:21Z","snapshot_observed_at":"2026-08-19T21:13:54.642373Z","submitted_at":"2024-06-16T10:47:21Z","title":"RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10890","snapshot_observed_at":"2026-08-15T22:53:25.053205Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.053205Z"},"links":{"cited_paper":"/paper/2406.10890","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:d4f87eeb287760668a4beecf546334677048a209184321ac7948ceec7c1548ca","observation_id":"18b24a09-19f4-4841-a360-f7e97fdef12c","resolution":{"observed_at":"2026-08-15T22:53:25.053205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.098157Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.098157Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:db00d5616a8c96bb0f1b187a480408623e3593213057c87a6d3daeb255a86a79","observation_id":"32e37a9d-2606-4437-9e32-a9e69af372b8","resolution":{"observed_at":"2026-08-15T22:53:25.098157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.103535Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.103535Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:a47398520f36550bbe633eec86ef16771a3cf0b506bab382e68cb3d6bf0a6d76","observation_id":"ef3d87a3-13f0-4869-9608-5982b97928ba","resolution":{"observed_at":"2026-08-15T22:53:25.103535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07933","last_updated":"2024-10-31T07:36:39Z","snapshot_observed_at":"2026-08-17T21:25:45.332072Z","submitted_at":"2024-06-12T06:56:20Z","title":"Large Language Model Unlearning via Embedding-Corrupted Prompts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07933","snapshot_observed_at":"2026-08-15T22:53:25.108280Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.108280Z"},"links":{"cited_paper":"/paper/2406.07933","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:4f60c40e056f94b509d1df3a953ef159b7ed2ffdb26964a9d211eccddff6aa55","observation_id":"7a66aa8a-26c1-475a-9e65-99eda234e334","resolution":{"observed_at":"2026-08-15T22:53:25.108280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06186","last_updated":"2024-06-10T11:31:04Z","snapshot_observed_at":"2026-08-19T21:13:55.146348Z","submitted_at":"2024-06-10T11:31:04Z","title":"A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks","version":1},"cited_work":{"arxiv_id":"2406.06186","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.06186","snapshot_observed_at":"2026-08-15T22:53:25.905169Z","title":"A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks","venue":"cs.CR","work_id":"35a51ba7-5e21-477e-94d7-0786f2c71571","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.112777Z"},"links":{"cited_paper":"/paper/2406.06186","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:8b3707badc168b5d87f0108e6e3dcf298e324dd31d29ab06cbb011dc22c9ff00","observation_id":"e5245fc1-75a1-4d18-ac21-a55b9975bfa9","resolution":{"observed_at":"2026-08-15T22:53:25.911379Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.20516","last_updated":"2024-07-30T03:26:09Z","snapshot_observed_at":"2026-08-20T06:57:18.296515Z","submitted_at":"2024-07-30T03:26:09Z","title":"Machine Unlearning in Generative AI: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.20516","snapshot_observed_at":"2026-08-15T22:53:25.118109Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.118109Z"},"links":{"cited_paper":"/paper/2407.20516","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:5e61d208e867fe88cd67c054a2e93a2209773ea1ac6fd58a65ddc2562183a4ef","observation_id":"76c54ef9-6cfa-4eaf-89b3-30ad689fe69c","resolution":{"observed_at":"2026-08-15T22:53:25.118109Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.803982Z","title":null,"venue":null,"work_id":"66f524e8-e323-4027-9095-d12a8dae5def","year":2022},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.122352Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:976015019dd71527d00f75d6239f0bbd0d4c1b7b117242a1e7c2d6bf8729f1bb","observation_id":"6f05630a-d756-4b43-ae5d-c027678d9b4e","resolution":{"observed_at":"2026-08-15T22:53:26.808332Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T22:53:26.659736Z","title":null,"venue":null,"work_id":"d8cd773b-fe4f-4a08-8608-8d8def7ebfad","year":2025},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.147466Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:2bdb0ccab90571a8dea166bc440bf818cd107a417c719e336cfb08548e26a3ba","observation_id":"ac2a9606-2c39-4b40-82b4-27b113d6c545","resolution":{"observed_at":"2026-08-15T22:53:26.723397Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.289428Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.289428Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:1a813ec7fd30f77f645e95c396b2a496528cbbfdc05bbe4cfdba726847eb419a","observation_id":"4f8a72e2-d39f-4a1a-8d9f-2d53a063e50f","resolution":{"observed_at":"2026-08-15T22:53:25.289428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.639885Z","title":null,"venue":null,"work_id":"aebf92ef-42c5-46ad-b0aa-f895a2d74678","year":2021},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.338878Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:e6d874ad3b07262988f3280f6ede977909b2a65c12a788f2bd4e640061d93b8e","observation_id":"895cf839-29e4-4984-aa66-e6d0fcccc548","resolution":{"observed_at":"2026-08-15T22:53:26.643274Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-15T22:53:25.341994Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.341994Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:e5123454135894d34cec5bc6247ae97c9bd14627de5e0a0a57c2336e51ffe2b1","observation_id":"41995507-bb87-47bc-948f-421fc5baa211","resolution":{"observed_at":"2026-08-15T22:53:25.341994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.519342Z","title":null,"venue":null,"work_id":"647c4925-2df0-47b0-bcbc-b6d264d91d0c","year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.346074Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:d2b9adaa0bac161a53415ca419f1b078f6bd7d839c929514f3b925e214be8fd5","observation_id":"c5fa9e99-5906-400a-8a6f-2eb900dae278","resolution":{"observed_at":"2026-08-15T22:53:26.631285Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07579","last_updated":"2024-06-06T06:31:08Z","snapshot_observed_at":"2026-08-21T22:14:38.761302Z","submitted_at":"2023-10-11T15:19:31Z","title":"In-Context Unlearning: Language Models as Few Shot Unlearners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07579","snapshot_observed_at":"2026-08-15T22:53:25.349283Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.349283Z"},"links":{"cited_paper":"/paper/2310.07579","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:766274df240a5d3ba67767416804dd9726d987240d73ab37ab4b83f89c1dbf2d","observation_id":"147bd5b7-41e4-4946-b4cd-3f0263bb345a","resolution":{"observed_at":"2026-08-15T22:53:25.349283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.352624Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.352624Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:5a355ac0f81b71ae8f4cdd950d1b0bc9aa54248f59651b66ca7831876af95263","observation_id":"66ebed2b-e0de-420a-9bcf-f9c0531d58fb","resolution":{"observed_at":"2026-08-15T22:53:25.352624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.452679Z","title":null,"venue":null,"work_id":"e4ba2731-6682-4f5b-8031-e342b58b1e23","year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.356092Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:27a11f47e5bfbc99bb27c3cb696e8d0ea8560e8d7b6a4f9cdd24657ef23ae252","observation_id":"a2045022-4b72-49e7-87b6-7667d799f6bb","resolution":{"observed_at":"2026-08-15T22:53:26.456116Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.06460","last_updated":"2024-07-14T20:14:02Z","snapshot_observed_at":"2026-08-22T11:39:17.601772Z","submitted_at":"2024-07-08T23:47:29Z","title":"MUSE: Machine Unlearning Six-Way Evaluation for Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.06460","snapshot_observed_at":"2026-08-15T22:53:25.360494Z","title":"Smith, and Chiyuan Zhang","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.360494Z"},"links":{"cited_paper":"/paper/2407.06460","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:2a4ce4638ea25051c6916ad9d70d382fb902ea4038981eabfbd9548093fe72c1","observation_id":"06a39523-be7b-4db6-bb71-93e88631fff1","resolution":{"observed_at":"2026-08-15T22:53:25.360494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.09261","last_updated":"2022-10-17T17:08:26Z","snapshot_observed_at":"2026-08-21T02:25:44.454471Z","submitted_at":"2022-10-17T17:08:26Z","title":"Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.09261","snapshot_observed_at":"2026-08-15T22:53:25.364420Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.364420Z"},"links":{"cited_paper":"/paper/2210.09261","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:27f3f71e8bb2643d054c402767f285ce26ea80e59740a3a199eeaf756f34aaf9","observation_id":"bf78693d-8c54-4448-8419-d160eb3a0c86","resolution":{"observed_at":"2026-08-15T22:53:25.364420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.439333Z","title":null,"venue":null,"work_id":"c8520365-426c-4980-9886-7145a7b5e060","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.368370Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:b29e33760c6011a9c1c509304d22f63217fa84f4db83e44c405034c1e4bd13dc","observation_id":"adfc2e8b-8d72-4f36-ad9b-8fa703ee1c14","resolution":{"observed_at":"2026-08-15T22:53:26.443948Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-15T22:53:25.372319Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.372319Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:e6301a564f0811bdb8ed59d56b3971c0e33589f26e31ee737ab59e0384b05744","observation_id":"023e9769-2a3e-4861-b5a5-0cd293ffe57c","resolution":{"observed_at":"2026-08-15T22:53:25.372319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.13054","last_updated":"2024-09-19T19:07:01Z","snapshot_observed_at":"2026-08-19T21:14:18.552784Z","submitted_at":"2024-09-19T19:07:01Z","title":"LLM Surgery: Efficient Knowledge Unlearning and Editing in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.13054","snapshot_observed_at":"2026-08-15T22:53:25.437024Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.437024Z"},"links":{"cited_paper":"/paper/2409.13054","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:651b5eba96ae1ebcaadbfef131d8aed59fc7bf718707148c95a96c46d17c8de9","observation_id":"aa5575bb-3130-43c6-8951-f11edc86a17d","resolution":{"observed_at":"2026-08-15T22:53:25.437024Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01983","last_updated":"2024-06-04T05:51:43Z","snapshot_observed_at":"2026-08-19T21:13:51.713796Z","submitted_at":"2024-06-04T05:51:43Z","title":"RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01983","snapshot_observed_at":"2026-08-15T22:53:25.496609Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.496609Z"},"links":{"cited_paper":"/paper/2406.01983","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:945a6964b3539d66b4c87d069992827f977338b1d3b2dc92f1e684fad2f1b2d6","observation_id":"17e295fb-5ff7-4ece-a9df-5c4fcd5ca9a0","resolution":{"observed_at":"2026-08-15T22:53:25.496609Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.424395Z","title":null,"venue":null,"work_id":"af0dc633-6165-4b3d-95ba-5bda444ae9fb","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.501025Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:5c071e794f1f28875062aeba81a2759528278b018fcaf37bf4f0af55fcc959d7","observation_id":"52679308-7e1b-4c03-8cc6-378f0668da83","resolution":{"observed_at":"2026-08-15T22:53:26.429906Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-15T22:53:26.354622Z","title":null,"venue":null,"work_id":"7359940e-1c32-40fe-9cad-b83ae7b9d717","year":2025},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.504850Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:7401d900a966e846f75029562d4bc2d03ef1cca8c7d994b08a7f058fc9e2ff9c","observation_id":"5075c10e-23d4-4dff-92af-5e3717f2c1ba","resolution":{"observed_at":"2026-08-15T22:53:26.402561Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.508091Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.508091Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:05cae4309429956497b07be2a9b71b5317161b42b48ad1c95f450bbd099b78c0","observation_id":"66c18c40-f2ad-4240-b858-28927781d95a","resolution":{"observed_at":"2026-08-15T22:53:25.508091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.317767Z","title":null,"venue":null,"work_id":"19bee75f-fe3e-47b5-8c26-145f6cdaf4e0","year":2025},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.511684Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:3f93b8d8ed1f84ffd1b51e48f51fb681eb3548efaba07a36523e1f6ef9832c69","observation_id":"c47e653e-e00d-4083-a944-11c245046cf3","resolution":{"observed_at":"2026-08-15T22:53:26.322135Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.515965Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.515965Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:178c66242ad811c7869d5277fa4c76b1826757cc22aa90c5ed68cb46931c261f","observation_id":"05d514bc-5e61-40e9-94bd-d059be422004","resolution":{"observed_at":"2026-08-15T22:53:25.515965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.520091Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.520091Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:74d72de2d4745e9af1f008a5978955d5642852fd0c1e4a14cfa179160da77107","observation_id":"c562c488-fb0d-4fb8-8238-0336b7b6b251","resolution":{"observed_at":"2026-08-15T22:53:25.520091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.524378Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.524378Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:fb0f3926dc16ff12fc37f7a8b24d387fad27a6efacb464340030639a1d24dc9f","observation_id":"8f9bb2e0-311a-473f-9c25-3eaf940d6466","resolution":{"observed_at":"2026-08-15T22:53:25.524378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.568188Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.568188Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:62e9b82327aacf3aca0db706d4f9af0df2edbcab2c6e805a46adf6354f5e13f4","observation_id":"ea93713d-e7b0-42b2-9a5a-ed6208d10150","resolution":{"observed_at":"2026-08-15T22:53:25.568188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.299982Z","title":null,"venue":null,"work_id":"37f994a5-777e-4914-a2e3-d8a333b879bf","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.614327Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:2d4f5da4893b5f974de6bbf0491fcde4c028315e0a80fa80e88fde7d93bb1c75","observation_id":"5e724a75-310d-461f-b88f-5dc3deddc8ef","resolution":{"observed_at":"2026-08-15T22:53:26.303338Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08109","last_updated":"2025-08-10T02:49:05Z","snapshot_observed_at":"2026-08-21T23:23:20.420099Z","submitted_at":"2024-10-10T16:56:05Z","title":"A Closer Look at Machine Unlearning for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08109","snapshot_observed_at":"2026-08-15T22:53:25.636143Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.636143Z"},"links":{"cited_paper":"/paper/2410.08109","citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:d561dcb80b19a83a4172515652cee4711ddbe0f3f3d659bcbf1f7bd159084ecf","observation_id":"e151f964-8a6c-408e-b547-626b67d17401","resolution":{"observed_at":"2026-08-15T22:53:25.636143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:26.202886Z","title":"Zhang, L","venue":null,"work_id":"0c665b13-ce39-4574-85ab-1fc0161a99ec","year":2024},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.641153Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:91948c73882249fff6e349c5333ac9a04b733fb2a26aec170f28a0ef298d4acb","observation_id":"967d3ed0-8b6e-4329-8f91-1757d8be1a99","resolution":{"observed_at":"2026-08-15T22:53:26.253463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.645254Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.645254Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:d8797ded6ea3a5327b037f8bd1a255b986072e25ba35857bb173a8772eb9119b","observation_id":"b32411d9-ae9d-490f-ab0b-e0e564b36465","resolution":{"observed_at":"2026-08-15T22:53:25.645254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:53:25.649814Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-15T22:53:25.649814Z"},"links":{"citing_paper":"/paper/2505.06027"},"observation_digest":"sha256:20512c3e544766321d502e8bebf577dda5b82615b8e7e9237c1e32e117fb4cd7","observation_id":"e0deaa01-4903-4c46-a146-1014940bea49","resolution":{"observed_at":"2026-08-15T22:53:25.649814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.06027","last_updated":"2025-05-09T13:19:09Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T20:16:20.655640Z","submitted_at":"2025-05-09T13:19:09Z","title":"Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":47,"verified_exact":2,"verified_fuzzy":1},"total_outbound_references":50},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2505.06027."}