{"as_of":"2026-08-17T15:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:722dab297ca277e5a412cf7e47440421f95f899ed8c76d03abf4b0babba26aeb","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:31:11.757305Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:58:48.617618Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T04:59:04.047606Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"cited_work":{"arxiv_id":"2504.12681","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.12681","snapshot_observed_at":"2026-08-07T04:59:04.047606Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","venue":"cs.CL","work_id":"b23eaf2d-f80a-4916-9e3a-9c2a332e6ff8","year":2025},"citing_paper":{"arxiv_id":"2506.09227","last_updated":"2025-06-10T20:30:39Z","snapshot_observed_at":"2026-08-14T07:33:23.070386Z","submitted_at":"2025-06-10T20:30:39Z","title":"SoK: Machine Unlearning for Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:58:48.617618Z"},"links":{"cited_paper":"/paper/2504.12681","citing_paper":"/paper/2506.09227"},"observation_digest":"sha256:91773dd372817110dc472627e395c57f80687998165006b398fadbf59185fd90","observation_id":"6580580b-ca44-477e-a9d7-ac923c97bf54","resolution":{"observed_at":"2026-08-07T04:59:04.124403Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.12681/citation-record","integrity":"/paper/2504.12681/integrity","json":"/paper/2504.12681/citation-record.json","paper":"/paper/2504.12681"},"outbound":[{"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":"2026-08-16T12:31:11.651962Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.651962Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:546ad33077608452dfffd3626de28e3e66bfe26d1831bc1915f9a0cb6d719799","observation_id":"eda1376e-8f15-4128-978c-e5865ad67780","resolution":{"observed_at":"2026-08-16T12:31:11.651962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.06196","last_updated":"2025-03-23T14:51:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-09T05:37:09Z","title":"Large Language Models: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06196","snapshot_observed_at":"2026-08-16T12:31:11.655921Z","title":"Large language models: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.655921Z"},"links":{"cited_paper":"/paper/2402.06196","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:4766692ac7b0c52e181587f7373ac19ae5b5a013161a9d44d0acbbf77c7a02cd","observation_id":"cf5bf2c4-ddaa-44ec-8ea5-057838779bdc","resolution":{"observed_at":"2026-08-16T12:31:11.655921Z","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":"2026-08-16T12:31:12.063943Z","title":"Large language models: A comprehensive survey on architectures, applications, and challenges,","venue":null,"work_id":"ae010796-9b1a-495b-86b1-ec8fa2660ecd","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.659560Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:2c6c9ef09c4ac5f0701488ca1541db98bda0c7be2d7a3ff8c0377e0b5b2dc216","observation_id":"3ac57010-8698-4768-b77c-f628ebf5d9d2","resolution":{"observed_at":"2026-08-16T12:31:12.067058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:12.055430Z","title":"Right to be forgotten in the age of machine learning,","venue":null,"work_id":"3666b996-dc13-4c3b-88e7-15d352ca0922","year":2021},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.662936Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:2cea4450adbb86360c45c1b691803240db1108354e7d4bf9a8bc134e9e02a77f","observation_id":"cfbd2349-1307-41b3-81aa-85e44821477e","resolution":{"observed_at":"2026-08-16T12:31:12.058565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:12.046536Z","title":"To forget or not? towards practical knowledge unlearning for large language models,","venue":null,"work_id":"dddd8f84-1c57-47a5-8896-5efbf681acb6","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.666292Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:79b74f70085cf4f6c05e443cf91186d5141eb1f643023d57bfeee7387f044079","observation_id":"6968543e-f425-4e81-b8e5-395dba967acf","resolution":{"observed_at":"2026-08-16T12:31:12.049638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08109","last_updated":"2025-08-10T02:49:05Z","snapshot_observed_at":"2026-08-16T13:10:37.588222Z","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":"2026-08-16T12:31:11.669353Z","title":"A closer look at machine unlearning for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.669353Z"},"links":{"cited_paper":"/paper/2410.08109","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:4facfbb70f1a8cb0a1426e3a71822419dc17568c1eb31e924c9094ccdbd17b1e","observation_id":"64339bba-c147-4139-8932-ba93389c9bb7","resolution":{"observed_at":"2026-08-16T12:31:11.669353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10223","last_updated":"2025-03-03T01:21:39Z","snapshot_observed_at":"2026-08-16T13:34:22.588125Z","submitted_at":"2024-07-14T14:26:17Z","title":"On Large Language Model Continual Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10223","snapshot_observed_at":"2026-08-16T12:31:11.673627Z","title":"Practical unlearning for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.673627Z"},"links":{"cited_paper":"/paper/2407.10223","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:52af9f716c7283c1c042dd747000f2da297c84dd74227a58b408753c9701832c","observation_id":"7d6b65a1-edc6-4a2b-8430-741c9f3ab512","resolution":{"observed_at":"2026-08-16T12:31:11.673627Z","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":"2026-08-16T12:31:12.038000Z","title":"Knowledge unlearning for mitigating privacy risks in language models,","venue":null,"work_id":"0b6523eb-c598-4970-81fd-9b217c6bc161","year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.677031Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:c18992f120b0cd1769643b97a20da9690faa6aa82ae71614642d1e06afb79227","observation_id":"ede333ff-ee1c-4866-8c67-784918d77e01","resolution":{"observed_at":"2026-08-16T12:31:12.041186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:12.029442Z","title":"Large language model unlearning,","venue":null,"work_id":"360b6354-bff4-4609-a855-e01230e77435","year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.680167Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:a710709ff9577588d30c39203f3e7570175c757eb41f82cc068a3ea5f55ea77f","observation_id":"9df92bdd-ab84-4daf-85d8-2d6d8bed8a86","resolution":{"observed_at":"2026-08-16T12:31:12.032566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:12.020947Z","title":"Unlearn what you want to forget: Efficient unlearning for LLMs,","venue":null,"work_id":"3d699c87-df3e-4920-a753-62734b1bfe2a","year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.683080Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:21375670baf65d6df0f107001c4864a45129d76193ff8a0f840020efee612a81","observation_id":"2417455c-fdf7-4a93-bac4-91d038d89ccb","resolution":{"observed_at":"2026-08-16T12:31:12.023936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:12.012383Z","title":"Towards safer large language models through machine unlearning,","venue":null,"work_id":"a7e9fa40-57c1-45be-a10f-41c7787c710d","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.686325Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:7b4a758252e5edd11252188e04a5533c89d988ee3067b54ed235620720e8bb5d","observation_id":"3e1f70d3-f20d-4ec2-a634-9adc0b5b33ad","resolution":{"observed_at":"2026-08-16T12:31:12.015603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10952","last_updated":"2025-02-11T01:46:13Z","snapshot_observed_at":"2026-08-16T13:42:33.254421Z","submitted_at":"2024-06-16T14:12:37Z","title":"Avoiding Copyright Infringement via Large Language Model Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10952","snapshot_observed_at":"2026-08-16T12:31:11.689632Z","title":"Avoiding copyright infringement via large language model unlearning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.689632Z"},"links":{"cited_paper":"/paper/2406.10952","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:4fa34f870c7af8b088e01e8a7015387e3ea0cbb98665f8ba5c085e1401db4986","observation_id":"058f2690-64e9-4d98-b34d-1d465a638020","resolution":{"observed_at":"2026-08-16T12:31:11.689632Z","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":"2026-08-16T12:31:12.003680Z","title":"United states code (usc),","venue":null,"work_id":"84e8a656-aa6c-4248-afde-60e42dd97f6e","year":2018},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.693185Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:8d768075ca8b8725993aa5bfb44a2b550b0ce5289a6720f34d5886408e5e12ec","observation_id":"3a16514f-4c0b-4e7c-8996-385f6ec6a0f0","resolution":{"observed_at":"2026-08-16T12:31:12.006858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.994962Z","title":"California consumer privacy act (ccpa),","venue":null,"work_id":"e1a45cb6-43cd-4533-9412-ef29f3ebb8c1","year":2018},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.696385Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:4ffbf124b0e0e5bf75892e3519ac30d2e068517c142b4dbcc75a80f8e145368d","observation_id":"d04e4554-9ef0-47ca-a350-c2f9433e548c","resolution":{"observed_at":"2026-08-16T12:31:11.998114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.986362Z","title":null,"venue":null,"work_id":"42e339af-d586-4a8f-a076-f05f2ba529ff","year":2016},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.699766Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:b4b87ae3220ee310f4249e0ace7f4f33c5d60bdfb895c55038f4c9f42e3b65fe","observation_id":"66434ec0-0ace-4278-8c1d-1733bd70f546","resolution":{"observed_at":"2026-08-16T12:31:11.989455Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.976836Z","title":"Abstract representations of associated emotions in the human brain,","venue":null,"work_id":"97d27c75-3f77-48f6-8b77-1513d88b6c41","year":2015},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.702905Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:f96303392e2bd452ce3616f09758e7cddec4da8af69ee9f7d382ae9ca2f61a5c","observation_id":"b4aa5997-6c7c-4b54-8b4e-b97083dc4d82","resolution":{"observed_at":"2026-08-16T12:31:11.979821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.968222Z","title":"Transformer feed-forward layers are key-value memories,","venue":null,"work_id":"5c69d3d7-665a-4c9f-b091-2c4c88dde70c","year":2021},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.706031Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:72f583e52f518c0da7ac2a45e10f1e80f00e2105319abe0e81196ab88d35aba0","observation_id":"02313584-ebc1-4bf0-815b-e69bae0031f8","resolution":{"observed_at":"2026-08-16T12:31:11.971657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.959625Z","title":"Locating and editing factual associations in gpt,","venue":null,"work_id":"336ab915-3202-4586-b9c3-24eaba1afdc8","year":2022},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.709197Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:4a895ba0e8ac725cf0c509ad8796d9c90e716be0f67f9ab4b1847b917c7a910d","observation_id":"8db0cc97-ee25-409d-a57e-3f7dbea78868","resolution":{"observed_at":"2026-08-16T12:31:11.962790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.950762Z","title":"Mass-editing memory in a transformer,","venue":null,"work_id":"a1c7d6ae-c10b-4e5b-8ee0-d31752d76558","year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.712388Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:33e251adf75dc82ec6b623ae01fc8a61fb9c34ad3676c34f7826bf7d72396e8d","observation_id":"55e6082a-88b9-48f7-aae4-938e38d607c3","resolution":{"observed_at":"2026-08-16T12:31:11.953959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.942205Z","title":"Ma- chine unlearning of pre-trained large language models,","venue":null,"work_id":"49779030-4f88-4866-a183-c352fdabbb0c","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.715651Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:54ce61827b8d9154b91fa69bb91a350150ec2362fc273c9112b91b6f9063c32a","observation_id":"fab14644-9306-45d5-8c4b-94f666327616","resolution":{"observed_at":"2026-08-16T12:31:11.945415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.933590Z","title":"Negative preference optimization: From catastrophic collapse to effective unlearning,","venue":null,"work_id":"1fa6dae9-029f-4524-9196-9a324ed306c2","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.718887Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:deab2ec6e932aaf7f7c1d46770f6cb4de10b03f8797646c63f7ca21ef16158f3","observation_id":"04d3a176-353e-42bd-8eeb-81df3194624e","resolution":{"observed_at":"2026-08-16T12:31:11.936873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.924965Z","title":"Eternal sunshine of the spotless net: Selective forgetting in deep networks,","venue":null,"work_id":"8633a096-0457-4bea-8e9c-445d628770ec","year":2020},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.722103Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:0738a37c69cfeafbe4c72e1aecced2435c4979921cb7632aaf4747755200ce91","observation_id":"bd0cea6f-11af-4d5b-a389-56dd5ba59a6e","resolution":{"observed_at":"2026-08-16T12:31:11.928240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.916038Z","title":"Knowledge unlearning for mitigating privacy risks in language models,","venue":null,"work_id":"a8600003-a898-4be6-89d8-27a03b80ee57","year":null},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.725366Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:9e7469a3bd290b6cc7b570d61fbf85644f4e2756b04ff49537ea028c28e00bbd","observation_id":"f4431aee-d7cd-4e98-8ad8-8e337bf43f88","resolution":{"observed_at":"2026-08-16T12:31:11.919280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.907085Z","title":"TOFU: A task of fictitious unlearning for LLMs,","venue":null,"work_id":"40da1958-cf3f-42c6-9660-e0e5087bd4eb","year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.728572Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:268d59e0cbb37e51f25c64932d237ecef80c998aa47c56921b7e2acd85ccca59","observation_id":"64a3762c-4df2-41e9-9cd6-80585732ae5f","resolution":{"observed_at":"2026-08-16T12:31:11.910202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.897776Z","title":"Unlearning bias in language models by partitioning gradients,","venue":null,"work_id":"e3ff7b2a-7d80-438f-a5ce-bead5bdbe1eb","year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.731903Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:7b14e20c3ef28a4ed39fc8870cb3ba81019a4a1f1d1c30945e5ca5a5a3cf9dcf","observation_id":"0be2b311-3b05-4de0-a547-a1d6a8ea10bc","resolution":{"observed_at":"2026-08-16T12:31:11.901192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.15152","last_updated":"2024-05-24T02:12:51Z","snapshot_observed_at":"2026-08-16T20:37:47.366182Z","submitted_at":"2024-05-24T02:12:51Z","title":"Machine Unlearning in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.15152","snapshot_observed_at":"2026-08-16T12:31:11.735012Z","title":"Machine unlearning in large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.735012Z"},"links":{"cited_paper":"/paper/2405.15152","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:2a8ca6bba951c223d7c2508d2b7289d2ef28db0b9cce7ac22e49f8c830bd3af1","observation_id":"2bc80d0d-6d21-4334-b60a-749744f3f715","resolution":{"observed_at":"2026-08-16T12:31:11.735012Z","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":"2026-08-16T12:31:11.887584Z","title":"Motion influence map for unusual human activity detection and localization in crowded scenes,","venue":null,"work_id":"4cef9611-47b3-4781-b403-741e84eeb10b","year":2015},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.738332Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:3b1d88280f2d300d22df78b327ff70da2ed47382d734a49ae4224a3b151f19e2","observation_id":"fe3ae82f-d614-4aaa-bd57-55ef170ad36a","resolution":{"observed_at":"2026-08-16T12:31:11.891159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.877816Z","title":"Deep reinforcement learning in continuous action spaces: a case study in the game of simulated curling,","venue":null,"work_id":"e397360f-64ce-4c46-9486-34f9b23b52a8","year":2018},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.741632Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:28c5252c7a61c2c5db5800022d1acce77083f5c881613313fd9109bb56dd5403","observation_id":"c5cc9756-2fca-49da-88c2-6f101c0080e4","resolution":{"observed_at":"2026-08-16T12:31:11.881265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.867701Z","title":"Continuous eeg decoding of pilots’ mental states using multiple feature block-based convolutional neural network,","venue":null,"work_id":"cb00c004-18d3-48b9-be9a-eea67484ade1","year":2020},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.744578Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:628770d57e1385f667237c7784cab7f1308c0d25d089d7519398e2cf90a7b017","observation_id":"957823fc-641c-40bb-99c1-1e2d1fa9ecce","resolution":{"observed_at":"2026-08-16T12:31:11.871178Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-16T12:31:11.747570Z","title":"Llama 2: Open foundation and fine-tuned chat models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.747570Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:9cdbd4bd7851bd86d1a4dde96cf41cb1ebc18e071b7c96624436d7cb028938c5","observation_id":"820d5f31-ec3f-42aa-bfb7-b0e621b9e313","resolution":{"observed_at":"2026-08-16T12:31:11.747570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-08-17T11:08:48.802438Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-16T12:31:11.750736Z","title":"Qwen2 technical report,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.750736Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:8cb31eb175a1edb5ff29f6a2235e8d84f4abcdb874fbd1eeb059d0ba49f9799d","observation_id":"89de9b06-e93b-437d-a1ab-922f95a539c0","resolution":{"observed_at":"2026-08-16T12:31:11.750736Z","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":"2026-08-16T12:31:11.857132Z","title":"LoRA: Low-rank adaptation of large language models,","venue":null,"work_id":"3079bca8-efae-4e95-83fb-f6fe41607f41","year":2022},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.754228Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:1d5e936cfc523801e2b078f94b5f63f6b81f1bf4958df710ceb3e81172128411","observation_id":"eff953e2-2897-4c18-89d6-086ca4c3f91f","resolution":{"observed_at":"2026-08-16T12:31:11.861544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:31:11.847242Z","title":"Fast model editing at scale,","venue":null,"work_id":"1d93152b-190e-4ff0-ab00-50ac57f1faa5","year":2022},"citing_paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T12:31:11.757305Z"},"links":{"citing_paper":"/paper/2504.12681"},"observation_digest":"sha256:0957a28327e92ffe7b0026bf9074be739c7d68d8e709fbde1256a9b637ef8983","observation_id":"14be5b13-bc26-410f-848d-648ee0001898","resolution":{"observed_at":"2026-08-16T12:31:11.851242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.12681","last_updated":"2025-04-17T06:16:32Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T12:23:05.165422Z","submitted_at":"2025-04-17T06:16:32Z","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":33},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2504.12681."}