{"as_of":"2026-08-08T13:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3efcddb33ad209bd5cd46a26d03f400e6db067e19584e9b133f6ceb89084746b","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T13:55:02.432445Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2509.05316/citation-record","integrity":"/paper/2509.05316/integrity","json":"/paper/2509.05316/citation-record.json","paper":"/paper/2509.05316"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:55:09.162713Z","title":"In: Proceedingsofthe34thInternationalConferenceonNeuralInformationProcessing Systems","venue":null,"work_id":"03030f3e-72e6-4d29-b060-3f482345675c","year":2020},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:58.519802Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:563eb3f5508139b02a4777ac447d49b55be653aa2c38b2c94af77e49ec6d0f4e","observation_id":"4b70818b-d1f3-43d5-9f4e-8850374580b1","resolution":{"observed_at":"2026-08-05T13:55:09.266821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:08.942496Z","title":"In: The Eleventh International Con- ference on Learning Representations (2023),https://openreview.net/forum?id= TatRHT_1cK","venue":null,"work_id":"c73a1a4f-7de2-4760-874b-839cc22e266a","year":2023},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:58.589185Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:92d57456884b52188d47f1f626e1542f7d07ea16e262f7dfe93e00489f120ba2","observation_id":"22b0066b-8c04-4725-8cd1-aa33e667b329","resolution":{"observed_at":"2026-08-05T13:55:09.043248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:08.752845Z","title":"In: 30th USENIX Security Symposium (USENIX Security 21)","venue":null,"work_id":"11712172-757f-4b75-a60e-ee35e33af1be","year":2021},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:58.705774Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:0d7e44135ec514a85dd6b36ce3d7e0697cf6a52329965434555125d607abc0ce","observation_id":"ab414a25-40f3-402c-9c7d-434356ec3e3a","resolution":{"observed_at":"2026-08-05T13:55:08.854588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:08.568068Z","title":"In: Che, W., Nabende, J., Shutova, E., Pilehvar, M.T","venue":null,"work_id":"65687079-fd94-4454-92c6-2c309900b646","year":null},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:58.854549Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:2c83cd6773190fe361aed545ffefa8469f19b132b4dae0e85a5b59bc8edd1da4","observation_id":"131b2afa-910c-4d5a-91d6-a2b3a898d232","resolution":{"observed_at":"2026-08-05T13:55:08.635059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.acl-long.1371","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:55:02.613550Z","title":"In: Che, W., Nabende, J., Shutova, E., Pilehvar, M.T","venue":null,"work_id":"9d9cdef1-3262-43af-8d12-b939d3083d39","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.127429Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:cd93996788e7fc58e89a0fc77915827faab1f023ad909e4fcacfc1a5d0971741","observation_id":"621bbbbb-5146-4073-a35b-19ae64d37a84","resolution":{"observed_at":"2026-08-05T13:55:02.677414Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04604","last_updated":"2025-01-08T05:24:50Z","snapshot_observed_at":"2026-08-04T14:31:04.378756Z","submitted_at":"2024-12-05T20:40:28Z","title":"ARC Prize 2024: Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04604","snapshot_observed_at":"2026-08-05T13:54:59.252066Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.252066Z"},"links":{"cited_paper":"/paper/2412.04604","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:6c5c5a623aad68aeac7676786286301b289994e45f22d41fad17e3f8af048b8a","observation_id":"51b163bb-74e6-4ed5-861a-442d2c71d529","resolution":{"observed_at":"2026-08-05T13:54:59.252066Z","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":"2026-08-05T13:55:08.344173Z","title":"com/locuslab/open-unlearning (2025), accessed: February 27, 2025","venue":null,"work_id":"b304724d-ca93-4c68-8b10-3d4a3bd784cb","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.396396Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:e3a2f4b3423096e71d159474ab7b04f80fecceb8d353ae1023e1ab2476608493","observation_id":"e5135c40-1b1e-4f54-87fc-490f75b1e728","resolution":{"observed_at":"2026-08-05T13:55:08.445441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:08.122392Z","title":null,"venue":null,"work_id":"bfe26ca1-4074-4265-964f-afe2d30f7bad","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.526524Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:b40a75a4a734fa61338deff8d6fa8d19d2c3c9d65f1eda7406121ff2075f81a6","observation_id":"de439379-7619-4929-bc7c-238fcde5f070","resolution":{"observed_at":"2026-08-05T13:55:08.217686Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:54:59.655496Z","title":"In: 2020 IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition (CVPR)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.655496Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:3e3ddb6b81e119ca8d6f4b45f9c623717e66b867a8e6ef5e656d901c0d035902","observation_id":"e27f72d9-9445-44b8-90d6-5a1cfe8fea44","resolution":{"observed_at":"2026-08-05T13:54:59.655496Z","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":"2026-07-06T18:55:11.576666Z","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":"2026-08-05T13:54:59.787082Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.787082Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:d1263980174d37f9b044488e04672bbd58eac562f0c38ea34ea9466266549d31","observation_id":"fe38c742-7228-4b99-9c73-f9362e5cf49b","resolution":{"observed_at":"2026-08-05T13:54:59.787082Z","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":"2026-08-05T13:54:59.912190Z","title":"In: International Con- ference on Learning Representations (2022),https://openreview.net/forum?id= nZeVKeeFYf9","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:59.912190Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:d7c11a1783be79be17feab9e30c9848e430d2c36dbb8eea059bd671e53d46b0d","observation_id":"cf2b9781-5476-4422-8caf-3a2b2e8f5574","resolution":{"observed_at":"2026-08-05T13:54:59.912190Z","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":"2026-08-05T13:55:00.010038Z","title":"In: Rogers, A., Boyd-Graber, J., Okazaki, N","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.010038Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:85d9786e7a7fb0de657731a407b6043060def10199b74efa3f59e991b8112f8f","observation_id":"9f63b326-2d95-484e-99ae-a55a1010e3ea","resolution":{"observed_at":"2026-08-05T13:55:00.010038Z","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":"2026-08-05T13:55:07.896041Z","title":"In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024), https://openreview.net/forum?id=tYdR1lTWqh","venue":null,"work_id":"3f9b86b5-33ae-4712-bf19-980856f89958","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.157709Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:479b365413544568608732bec6b71ab040e10357f2f68e80a57b1d0434157f10","observation_id":"284d5597-36ec-4214-a2f3-debbb9780c91","resolution":{"observed_at":"2026-08-05T13:55:08.000943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:07.680199Z","title":"In: The Thirty-eight Conference on Neural Information Processing Sys- tems Datasets and Benchmarks Track (2024),https://openreview.net/forum? id=wOmtZ5FgMH Standard vs","venue":null,"work_id":"ccb1c8b9-30fe-4f18-b6f0-d5ab39804e80","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.311837Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:a11449b4bd02e8a86226e030a5b0dc1416e5a3bb17682845fb485ae579cca7d6","observation_id":"0be7bd39-c607-4f76-ade3-2487d96fe3f5","resolution":{"observed_at":"2026-08-05T13:55:07.780657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:07.399190Z","title":"In: Sec- ond Conference on Language Modeling (2025),https://openreview.net/forum? id=Kd97lfFfTu","venue":null,"work_id":"b4e94369-5950-4674-992b-f40378266c42","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.432426Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:e34fe87ded048f504c54b36dac4f3d49671509cc1a4d14317e34a193bf39a203","observation_id":"7d1a802b-2558-4ba8-9f2b-54824be24f95","resolution":{"observed_at":"2026-08-05T13:55:07.561223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:00.587663Z","title":"In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.587663Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:fd67b410a78ec5f5d069048ad110b51c85d20d70e5f2f8ecf10e183c019c11ea","observation_id":"c250bd80-6131-4436-854d-cc588e855097","resolution":{"observed_at":"2026-08-05T13:55:00.587663Z","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":"2026-08-05T13:55:07.097990Z","title":"In: Proceedings of the 41st Inter- national Conference on Machine Learning","venue":null,"work_id":"f4c4a4e8-f4ad-420e-8f10-f6bf74771258","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.712011Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:c7283e5116e1880a96257c789ee48e73b9b05c92a8e020e2ffff25d09a9d540f","observation_id":"8d1b9631-49fc-4ebf-9810-2574234581d1","resolution":{"observed_at":"2026-08-05T13:55:07.229102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:06.868739Z","title":"In: Text Summarization Branches Out","venue":null,"work_id":"b02415c0-09b2-4f21-aa66-2e363128c3e8","year":2004},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.816375Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:3ad2c537e3c6e9ddbf0a28ab61c7ef1772bae33732b88d0c6f721210c24aec7d","observation_id":"d0477187-4615-4609-bac0-18b557484995","resolution":{"observed_at":"2026-08-05T13:55:06.980212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.12817","last_updated":"2022-08-13T23:35:30Z","snapshot_observed_at":"2026-07-06T12:51:51.647366Z","submitted_at":"2022-03-24T02:40:33Z","title":"Continual Learning and Private Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.12817","snapshot_observed_at":"2026-08-05T13:55:00.880030Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.880030Z"},"links":{"cited_paper":"/paper/2203.12817","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:ea0deb01d2e79ce7beb19c77141d0a97b21322f6bf5bbfc7a515c51f1f33d6f7","observation_id":"86a5d8cc-41a5-4e0b-a85a-53e750d85a51","resolution":{"observed_at":"2026-08-05T13:55:00.880030Z","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":"2026-08-05T13:55:00.958060Z","title":"Nature Machine Intelligence 7, 181–194 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:00.958060Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:77b786b2a41495b1704e54e64ae6ca7221558c15a39fb0004bd4856afce9e7f6","observation_id":"ad40f035-8ad0-47a2-8129-7255eb3644d4","resolution":{"observed_at":"2026-08-05T13:55:00.958060Z","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":"2026-08-05T13:55:01.056132Z","title":"In: Proceed- ings of the 2024 Conference on Empirical Methods in Natural Language Process- ing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.056132Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:73587d292b75d4655788c1926ce1ba42447f9c09d0b20a6c87b3b1203daed599","observation_id":"73116815-f353-46c0-82bb-0bd73b3ea877","resolution":{"observed_at":"2026-08-05T13:55:01.056132Z","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":"2026-08-05T13:55:06.637496Z","title":"In: First Conference on Language Modeling (2024), https://openreview.net/forum?id=B41hNBoWLo","venue":null,"work_id":"ce2249ad-423c-4bac-9f86-b20a503c4d69","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.122714Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:a00de27664acf93cad749f7b7db7a439189badf5e49c8e07f60f6f5012bdf16c","observation_id":"de6c79cf-c074-4347-9378-40d1ade15427","resolution":{"observed_at":"2026-08-05T13:55:06.765088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:06.385154Z","title":"In: Proceedings of the 31st International Con- ference on Computational Linguistics","venue":null,"work_id":"94ac73a2-c3db-44df-b638-0ca6571e23d0","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.166683Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:82d524c538842d7f0649f60ef20cc00a61114b7c881233718eccde8b4db5e583","observation_id":"f557a0ca-1c10-4d44-b41f-fe226e543617","resolution":{"observed_at":"2026-08-05T13:55:06.490222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:06.069613Z","title":"Transactions on Machine Learning Research (2025),https://openreview","venue":null,"work_id":"659e7ec0-d10f-44af-89b9-2d4bd041d6d8","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.221510Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:98430a0f3b874d33e8ed4aefcfabe9c13bf9a0d43b9bd68ead01663bf9f5b0ef","observation_id":"c75212f0-ac45-4382-a88d-c26b4a7db34f","resolution":{"observed_at":"2026-08-05T13:55:06.233087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:05.795002Z","title":"In: Rosen- thal, S., Rosá, A., Ghosh, D., Zampieri, M","venue":null,"work_id":"002bed93-d494-4733-a2ac-e0f7c8d05a0a","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.284050Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:8610902914124d8868bc39ce0080e92848333d022bf6f0d57ffa9aad328ed57f","observation_id":"09812346-418c-47dc-81b0-e0551807476a","resolution":{"observed_at":"2026-08-05T13:55:05.925942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16810","last_updated":"2025-03-10T21:33:53Z","snapshot_observed_at":"2026-07-06T18:36:12.298104Z","submitted_at":"2024-06-24T17:22:36Z","title":"How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.16810","snapshot_observed_at":"2026-08-05T13:55:01.349922Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.349922Z"},"links":{"cited_paper":"/paper/2406.16810","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:52b92168526b015cf75116e23c7895efe2a77568c5435ace0f2f4c5b71cd0319","observation_id":"627142d9-09d7-4f34-a78b-efc15e335f0b","resolution":{"observed_at":"2026-08-05T13:55:01.349922Z","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":"2026-08-05T13:55:05.535263Z","title":"In: Pro- ceedings of the 37th International Conference on Neural Information Processing Systems","venue":null,"work_id":"184859be-46d6-4d1a-a59e-c35c9c565f92","year":2023},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.427606Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:e6c8f31fc0e0174fceea8ad8aa2cd2a354e1810e901902fe48a337b04e74da5e","observation_id":"ca0132d4-263f-4bb1-a760-72eabfa543a1","resolution":{"observed_at":"2026-08-05T13:55:05.671756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:05.248444Z","title":"In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)","venue":null,"work_id":"229fd8d7-d601-4a17-8b50-a02eb5c722c0","year":2019},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.484081Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:01f0ec5db0ee02bc8a5ee4ace66d77ae6341986da898c7913de37d72710257d9","observation_id":"518c836e-ffd4-4ed8-88cb-798bfcea5c4e","resolution":{"observed_at":"2026-08-05T13:55:05.399869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:04.986746Z","title":"In: The Twelfth International Conference on Learning Representations (2024),https://openreview.net/forum? id=kmn0BhQk7p","venue":null,"work_id":"18be01d6-8be8-48f2-bc22-0585249ea0c6","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.549290Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:0dd0835ea455618556eaba53d1bbe3488f914a7f78423c6f92426db2a8af6500","observation_id":"a0b5d9f8-5be6-4381-9cef-ed7809cee454","resolution":{"observed_at":"2026-08-05T13:55:05.119161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02879","last_updated":"2025-04-08T17:18:21Z","snapshot_observed_at":"2026-08-03T18:08:46.616396Z","submitted_at":"2024-10-03T18:07:25Z","title":"Position: LLM Unlearning Benchmarks are Weak Measures of Progress","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02879","snapshot_observed_at":"2026-08-05T13:55:01.621509Z","title":"org/abs/2410.02879","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.621509Z"},"links":{"cited_paper":"/paper/2410.02879","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:87ce7ccb0966f9ae0371a170904455cc8c2d765b4ed4534ec90a4cf8dee8e5fe","observation_id":"7c6d5820-0f5c-4050-a7ac-296383202121","resolution":{"observed_at":"2026-08-05T13:55:01.621509Z","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":"2026-08-05T13:55:04.803631Z","title":"In: Oh,A.H.,Agarwal,A.,Belgrave,D.,Cho,K.(eds.)AdvancesinNeuralInformation Processing Systems (2022),https://openreview.net/forum?id=u3vEuRr08MT","venue":null,"work_id":"66b994c3-4edf-4796-85cd-40273d8ce8b2","year":2022},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.738329Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:e7e03c7e92d654237733d34eab10b56a5cb13e1afc2fc953d928d896c634c342","observation_id":"2d6c706c-0883-4c76-bb39-0b7c9eac5353","resolution":{"observed_at":"2026-08-05T13:55:04.885774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:01.824289Z","title":"In: Proceedings of the 31st International Conference on Neural Information Processing Systems","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.824289Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:3462a001e6c1fc508ea81a9de4f5412b6f049e6b59e381dfb3ebc6062401050d","observation_id":"9db2e64c-55de-4bd5-aa8e-c6ad80c2c574","resolution":{"observed_at":"2026-08-05T13:55:01.824289Z","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":"2026-08-05T13:55:04.561433Z","title":"In: The Thirteenth International Conference on Learning Representations (2025),https: //openreview.net/forum?id=huo8MqVH6t","venue":null,"work_id":"6e8c3577-31ce-4e6b-b87d-690d4f8e2e5b","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.882647Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:2e6435741936bbd248d7816858aaedfe94279fe2ed110464d3bab928a8704638","observation_id":"fab1e539-6023-452d-87ef-efdbec717909","resolution":{"observed_at":"2026-08-05T13:55:04.653025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01574","last_updated":"2024-11-06T02:54:00Z","snapshot_observed_at":"2026-08-06T00:29:17.674418Z","submitted_at":"2024-06-03T17:53:00Z","title":"MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01574","snapshot_observed_at":"2026-08-05T13:55:01.947238Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:01.947238Z"},"links":{"cited_paper":"/paper/2406.01574","citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:8a3b6bcc6c388a0a486fb74e4ae146acedac8730b7dbe5a2bf98bbc7c218c8b2","observation_id":"3c90f828-096b-480c-bf77-958bc06d5451","resolution":{"observed_at":"2026-08-05T13:55:01.947238Z","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":"2026-08-05T13:55:04.279472Z","title":"In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024),https:// openreview.net/forum?id=8Dy42ThoNe","venue":null,"work_id":"5384ed2c-c4f7-40ea-91b6-8d451500d0c0","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.019920Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:5041ee9268bc8fdbc9e8bd39f9ab0d347ee7ea5f11c390105ec224784a7395e7","observation_id":"912451e0-fadd-4070-9ae0-8f91e5d00818","resolution":{"observed_at":"2026-08-05T13:55:04.411831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:04.028550Z","title":"In: The Thirteenth International Con- ference on Learning Representations (2025),https://openreview.net/forum?id= Q1MHvGmhyT","venue":null,"work_id":"cea46e19-0fff-4977-a531-b17104e0c7a5","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.085945Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:91ab6b8dc77bc2489aaea771c483d6c12ab7b96b2c9e7c55d7eec17f67465f16","observation_id":"b8ac810d-2f42-4efe-b558-b0679b95ce67","resolution":{"observed_at":"2026-08-05T13:55:04.101957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:02.190516Z","title":"(eds.) Proceedings of the 57th Annual Meeting of the Association for Com- putational Linguistics","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.190516Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:35dbc68c76e1119a48d49774cd9a3a9a752c715ffd348cf511fb53e3ca2a8fcd","observation_id":"7aa6a031-3eb6-4572-85de-c18b43a7674c","resolution":{"observed_at":"2026-08-05T13:55:02.190516Z","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":"2026-08-05T13:55:03.827404Z","title":"In: First Conference on Language Modeling (2024), https://openreview.net/forum?id=MXLBXjQkmb Standard vs","venue":null,"work_id":"d7208762-8593-4536-bb05-99ea665a7dbf","year":2024},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.280253Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:68bd961e04d0ee040598073a4d319b1b2b8e6b43923304d8e2fedad8fb2a875c","observation_id":"c5a48b5f-af62-40c5-a8e1-db8ce73780a1","resolution":{"observed_at":"2026-08-05T13:55:03.927818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2017.80544","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:55:03.124521Z","title":"name\": name of the person,","venue":null,"work_id":"ac798c40-5960-4382-8091-762c930605a6","year":2017},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.338738Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:66fc8cb97b299a55fed009668c26852cfe93bfec966fa4c2ee098f01116880d3","observation_id":"cc1285c1-7f53-4145-bf2b-a8933a4e0402","resolution":{"observed_at":"2026-08-05T13:55:03.196991Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T13:55:03.586481Z","title":"ROUGE-L provides the longest sequence overlap and the verbatim memory of the Unlearned Model(M ; θ∗)","venue":null,"work_id":"e9cbbddc-7cda-41f0-9d6b-8bb7ae1a26b8","year":null},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:02.432445Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:1dec926455c5ceda42fae4e44c8350d4d2420fdcdc17d10ddb454b6aa2f8e3ad","observation_id":"45980714-2cc5-4cec-9ef7-467c5cad5abb","resolution":{"observed_at":"2026-08-05T13:55:03.653398Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.findings-acl.310","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:55:02.824852Z","title":"5966–5982","venue":null,"work_id":"98f67aae-c75e-4646-bd8a-75afea64e40f","year":2025},"citing_paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-05T13:54:58.977531Z"},"links":{"citing_paper":"/paper/2509.05316"},"observation_digest":"sha256:2e57025e9afb84dbbd6b6a83a431ac8f6f2cff5e65fefa3d0a8fe78d9ddb69e2","observation_id":"51556dbf-1532-4096-9513-88fa96eff6c8","resolution":{"observed_at":"2026-08-05T13:55:02.885319Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.05316","last_updated":"2026-06-05T13:49:14Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T21:27:31.671223Z","submitted_at":"2025-08-29T19:25:52Z","title":"Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":15,"verified_exact":2,"verified_fuzzy":23},"total_outbound_references":41},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2509.05316."}