{"as_of":"2026-08-15T04:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3f02297c05ad6b54fe82bb83c7ca281c729e542426bda1e64b328b9051cc1244","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T19:54:19.224601Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:27:30.924737Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T02:07:33.490588Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.10242","snapshot_observed_at":"2026-08-07T10:27:30.924737Z","title":"Measuring non-adversarial re- production of training data in large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05126","last_updated":"2025-06-05T15:13:57Z","snapshot_observed_at":"2026-08-15T02:33:46.613835Z","submitted_at":"2025-06-05T15:13:57Z","title":"Membership Inference Attacks on Sequence Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T10:27:30.924737Z"},"links":{"cited_paper":"/paper/2411.10242","citing_paper":"/paper/2506.05126"},"observation_digest":"sha256:8cdb160ac769dda078fdc75102413c14aec128a8536c55047fbb640667d533aa","observation_id":"554a1aab-d4a9-4732-b58f-c68ceb5c21c6","resolution":{"observed_at":"2026-08-07T10:27:30.924737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"cited_work":{"arxiv_id":"2411.10242","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.10242","snapshot_observed_at":"2026-07-03T02:07:33.490588Z","title":"Measuring non-adversarial repro- duction of training data in large language models","venue":null,"work_id":"0c6b7885-cc2e-46ec-b86f-a49f7aa43027","year":2024},"citing_paper":{"arxiv_id":"2606.06286","last_updated":"2026-06-04T15:25:24Z","snapshot_observed_at":"2026-08-13T08:39:08.171099Z","submitted_at":"2026-06-04T15:25:24Z","title":"LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-06-28T01:40:53.284131Z"},"links":{"cited_paper":"/paper/2411.10242","citing_paper":"/paper/2606.06286"},"observation_digest":"sha256:e0c89bdc9c77f4a471e7853e7b240a976821e64712525c6a764bc3790df2d215","observation_id":"125ac473-0634-420a-81d4-4ca8f561fee9","resolution":{"observed_at":"2026-07-02T12:56:57.472921Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"cited_work":{"arxiv_id":"2411.10242","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.10242","snapshot_observed_at":"2026-07-03T02:07:33.490588Z","title":"Measuring non-adversarial repro- duction of training data in large language models","venue":null,"work_id":"0c6b7885-cc2e-46ec-b86f-a49f7aa43027","year":2024},"citing_paper":{"arxiv_id":"2606.10091","last_updated":"2026-06-08T19:16:58Z","snapshot_observed_at":"2026-08-05T00:07:01.562006Z","submitted_at":"2026-06-08T19:16:58Z","title":"SoK: Colluding Adversaries in Machine Learning Pipelines","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T16:10:51.471822Z"},"links":{"cited_paper":"/paper/2411.10242","citing_paper":"/paper/2606.10091"},"observation_digest":"sha256:9d004396d5f4d60f1725b05ddbcdf59c8b9a5771621add1f893a1fd9841f0c3f","observation_id":"403014c9-b9b9-47b7-a38c-6620ed20f3eb","resolution":{"observed_at":"2026-07-03T02:07:33.492459Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.10242/citation-record","integrity":"/paper/2411.10242/integrity","json":"/paper/2411.10242/citation-record.json","paper":"/paper/2411.10242"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T19:54:19.935150Z","title":null,"venue":null,"work_id":"ffa4a598-b3a1-4cbe-92af-d61ce1e7daf9","year":2024},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.138509Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:acec90501c307c6c5aa3f8a11f9a8544d86de958bfda9638c950c39c9be09c84","observation_id":"21709886-3c2e-409c-bd6c-67600f594df9","resolution":{"observed_at":"2026-08-12T19:54:19.940546Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.840072Z","title":"black hole","venue":null,"work_id":"20151465-3c2b-4558-b135-36608cb2b269","year":1916},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.177600Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:bfb223a4d5ba0bb581d45e45d2dffa5aad40eefc72c492b7bbefa9246e19a487","observation_id":"df1b763a-cafb-46bb-8611-068f4f2266d6","resolution":{"observed_at":"2026-08-12T19:54:19.845550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.912327Z","title":"Table 3: Model-specific instantiation of the assistant prompt","venue":null,"work_id":"c0528ab1-676d-4903-8672-54f2541d57dd","year":2023},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.148620Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:e63eb483743df8c3a770f58cb98ccc8e2f3a5892d052fc8844ad750094ff28bb","observation_id":"1f4c4e58-dbc3-4fee-966d-21d868eb3749","resolution":{"observed_at":"2026-08-12T19:54:19.918726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-12T19:54:19.039863Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.039863Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:5f6690c618852a40913896dd04c5e346f159528e54f532212cbe21cd955b2b0c","observation_id":"45043830-e10c-419f-b9cc-39d2afefb6a7","resolution":{"observed_at":"2026-08-12T19:54:19.039863Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04265","last_updated":"2025-01-12T05:32:57Z","snapshot_observed_at":"2026-08-14T07:35:26.602225Z","submitted_at":"2024-10-05T18:55:01Z","title":"AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04265","snapshot_observed_at":"2026-08-12T19:54:19.056145Z","title":"Ai as humanity’s salieri: Quantifying linguistic creativity of language models via systematic attribution of machine text against web text","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.056145Z"},"links":{"cited_paper":"/paper/2410.04265","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:c77ab19650fb8202f23d6a5e277fd3f8b4e7f42e6b1b0896bc8eafeaf348df19","observation_id":"719ccea3-9be8-4c00-8a33-b6b979c14df3","resolution":{"observed_at":"2026-08-12T19:54:19.056145Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17035","last_updated":"2023-11-28T18:47:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-28T18:47:03Z","title":"Scalable Extraction of Training Data from (Production) Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17035","snapshot_observed_at":"2026-08-12T19:54:19.063840Z","title":"doi: 10.1162/tacl_a_00567","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.063840Z"},"links":{"cited_paper":"/paper/2311.17035","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:5d38860115d3203c10ca45200da87da607e9943b0e905b1fcf1d151a66d029a1","observation_id":"879f1fd6-c7ff-43ed-9aa6-03c03bb0821a","resolution":{"observed_at":"2026-08-12T19:54:19.063840Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12034","last_updated":"2024-11-05T10:24:42Z","snapshot_observed_at":"2026-08-12T23:31:45.658910Z","submitted_at":"2024-06-30T22:18:49Z","title":"Understanding Transformers via N-gram Statistics","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12034","snapshot_observed_at":"2026-08-12T19:54:19.071209Z","title":"Understanding transformers via n-gram statistics","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.071209Z"},"links":{"cited_paper":"/paper/2407.12034","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:b4e35faa1de342dd82910e2578e6b6f55490e74fdba16219ad085ebaa2a3896e","observation_id":"ab1e3ec1-9963-45f9-ba81-a7f4da1e23a1","resolution":{"observed_at":"2026-08-12T19:54:19.071209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05196","last_updated":"2024-07-01T16:36:30Z","snapshot_observed_at":"2026-08-13T10:16:58.264595Z","submitted_at":"2023-09-11T02:16:47Z","title":"Does Writing with Language Models Reduce Content Diversity?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05196","snapshot_observed_at":"2026-08-12T19:54:19.077929Z","title":"Does writing with language models reduce content diversity? arXiv preprint arXiv:2309.05196,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.077929Z"},"links":{"cited_paper":"/paper/2309.05196","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:0d86e863248d8dd138b0abb5cb6c03a185d7dc2fc884bff0a6246267635d90bd","observation_id":"46931ed1-aedc-402f-a259-8367be1cedc8","resolution":{"observed_at":"2026-08-12T19:54:19.077929Z","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":"2026-08-12T19:54:20.031957Z","title":"Privacy risks of general-purpose language models","venue":null,"work_id":"89c27ebd-ed73-4ce7-b615-2a4878115174","year":2020},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.083846Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:6908b5bcf5c8ae15e99a2a5b85e35ca39bf0379572c2f1bacaf9783a7c7b7589","observation_id":"cab7f8e7-8327-48b5-841a-24cea1494a33","resolution":{"observed_at":"2026-08-12T19:54:20.037587Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.088940Z","title":"Membership inference attacks against machine learning models","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.088940Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:3aa80d2cd5b3bba2fdae055e61ef073c7b01882535858e2cc6a3f791d8bb369a","observation_id":"5686168c-ff99-4abf-903b-be182c3c0e6a","resolution":{"observed_at":"2026-08-12T19:54:19.088940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11817","last_updated":"2025-02-13T08:11:25Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-22T10:26:14Z","title":"Hallucination is Inevitable: An Innate Limitation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.11817","snapshot_observed_at":"2026-08-12T19:54:19.100984Z","title":"Under review","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.100984Z"},"links":{"cited_paper":"/paper/2401.11817","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:b6e445ec2ee85ec3b3a9b3182f8cc8279f0489f674aba5d38f2a349296ae152d","observation_id":"e45a8618-8020-4f42-badc-8788c80c57c1","resolution":{"observed_at":"2026-08-12T19:54:19.100984Z","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":"2026-08-12T19:54:19.106680Z","title":"Privacy risk in machine learning: Analyzing the connection to overfitting","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.106680Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:d4515f2847063a2a62f918bb81957a49facf1bda929efbf6d50371f76fabf3c4","observation_id":"15a014cc-466d-4ad5-a6c6-1205169705b3","resolution":{"observed_at":"2026-08-12T19:54:19.106680Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.11998","last_updated":"2024-03-10T19:34:57Z","snapshot_observed_at":"2026-08-13T10:08:28.290453Z","submitted_at":"2023-09-21T12:13:55Z","title":"LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.11998","snapshot_observed_at":"2026-08-12T19:54:19.118870Z","title":"P Xing, Joseph E","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.118870Z"},"links":{"cited_paper":"/paper/2309.11998","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:593224d5e1d6f086630d6656983d0ac88cf32e2cbd89800ae7cd959b33ee3476","observation_id":"3a237033-3545-44c2-a880-502820b76ff3","resolution":{"observed_at":"2026-08-12T19:54:19.118870Z","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":"2026-08-12T19:54:19.976798Z","title":"Under review","venue":null,"work_id":"498bc60e-c42e-4d13-858a-d6d2e177bd70","year":2023},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.124524Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:c764108a2ffd5dbad6a10bc75c708a3326b024ebad6e572f68911b036ebba0ff","observation_id":"529fbcb9-265c-43c0-9e7f-ca19810b8aef","resolution":{"observed_at":"2026-08-12T19:54:19.983866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.886851Z","title":"Copy this text:","venue":null,"work_id":"e84c25d9-6884-4a74-99de-65d71063bf56","year":2023},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.159515Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:9a56e265414f23d7e5962ea495446bd2f183081336e7175126d557045697b041","observation_id":"2c1f8d55-e481-455c-9f1f-667dbf250cf6","resolution":{"observed_at":"2026-08-12T19:54:19.893700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.863198Z","title":"Under review","venue":null,"work_id":"dfb35f78-6f1d-420c-b718-4ad9979b450a","year":1986},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.169837Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:09fc4c95d5a4cbd36adf846ca3ff7a37870407b82bd1af6d82f5863c82db071d","observation_id":"c7d73801-61d1-4ab4-b101-f365967ca516","resolution":{"observed_at":"2026-08-12T19:54:19.870065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"status/9018327","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T19:54:19.379078Z","title":"yolov3.weights","venue":null,"work_id":"c0f13928-8e6a-4bed-8201-15f38ab9fb01","year":2000},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.188411Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:4cbde048a249116a8cfbdcd64f617f70be92a796a042591cd84b102b4a99d75c","observation_id":"06a26a10-f2e8-4482-a1c0-33fb45af7edb","resolution":{"observed_at":"2026-08-12T19:54:19.393617Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.803069Z","title":"Claude 3.5 Sonnet generated the following text for the prompt “Write a news article about The Catalan declaration of independence","venue":null,"work_id":"f075149b-0254-4bf4-af44-ff3f613a56e4","year":2017},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.206186Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:4a5cfaf908fb8d8ecb65ffc94463f6c5b633d40c92457e55d94aad38fed9f746","observation_id":"0b3aa300-1b00-45ea-9e49-13a499cdd9f4","resolution":{"observed_at":"2026-08-12T19:54:19.809539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.780162Z","title":"Spain is living through a sad day,","venue":null,"work_id":"c1f7818c-efcc-4aae-b60f-3d906217ae00","year":1976},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.217979Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:f517ec4de64890dadd46f309ac045f48cca0f3e96e2520c5f277719cbb5ea2a4","observation_id":"86472ce6-af98-45d8-b64f-473465a07804","resolution":{"observed_at":"2026-08-12T19:54:19.787332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.760774Z","title":"Schindler’s List","venue":null,"work_id":"2a698ced-2cd9-49ff-b875-bc8c7ac3937b","year":1993},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.224601Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:02844d23776e2125ce74db6973596dc94fc8b314aeced63fd6ab18355d90bba3","observation_id":"87e7825d-a9e5-4939-831d-2c7126129d41","resolution":{"observed_at":"2026-08-12T19:54:19.766889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.954661Z","title":"independent writing","venue":null,"work_id":"1947d3d3-d2b9-45cd-9bde-972730b32120","year":2021},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":500,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.131145Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:5268e387cde41c7804b38475c4b190e4fe860b23d8f8bdf84a648cf1213d04b4","observation_id":"e7d930df-587d-4a9d-8113-997c31af06d0","resolution":{"observed_at":"2026-08-12T19:54:19.960530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T19:54:19.821859Z","title":"This detection is the beginning of a new era: The field of gravitational wave astronomy is now a reality,","venue":null,"work_id":"67930a26-1463-44cc-bedd-18ca0adf915b","year":1916},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.199566Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:87db06bf4f2543430be551c927ad0fd3e479c2f85a241cad79842a0d64715a9e","observation_id":"024b0ba4-f64d-4789-b71c-86678b6bde7d","resolution":{"observed_at":"2026-08-12T19:54:19.827471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-08-14T18:15:53.516440Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-12T19:54:19.095661Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.095661Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:5a544887eb148a69727eaac85e482fe5ad4498c3073b9dc44c6d94a044a51d7a","observation_id":"27fa27ef-cd25-4ad3-8fca-2e4c18e65cd9","resolution":{"observed_at":"2026-08-12T19:54:19.095661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01470","last_updated":"2024-05-02T17:00:02Z","snapshot_observed_at":"2026-08-13T13:43:58.816757Z","submitted_at":"2024-05-02T17:00:02Z","title":"WildChat: 1M ChatGPT Interaction Logs in the Wild","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.01470","snapshot_observed_at":"2026-08-12T19:54:19.113181Z","title":"Wildchat: 1m chatgpt interaction logs in the wild","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.113181Z"},"links":{"cited_paper":"/paper/2405.01470","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:e2784eaad8c666689626c433caaad9107cd183384a60c725a9e9c429a0d8f771","observation_id":"5253d434-45fd-4aa2-b207-8f84c77fc6cc","resolution":{"observed_at":"2026-08-12T19:54:19.113181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07646","last_updated":"2023-03-06T06:28:18Z","snapshot_observed_at":"2026-08-03T19:51:05.627063Z","submitted_at":"2022-02-15T18:48:31Z","title":"Quantifying Memorization Across Neural Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.07646","snapshot_observed_at":"2026-08-12T19:54:19.032446Z","title":"Membership inference attacks from first principles","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.032446Z"},"links":{"cited_paper":"/paper/2202.07646","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:12a1af78fb42044893bf20e0f15978b42604bd9b5697d108c962569ddc6b45f6","observation_id":"6f5bd5f6-c68b-4d34-893d-f6464c6be5ef","resolution":{"observed_at":"2026-08-12T19:54:19.032446Z","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":"2026-08-12T19:54:20.059340Z","title":"Reconstructing training data with informed adversaries","venue":null,"work_id":"dab76514-96d3-4d93-a8b1-c0f1ac933264","year":2022},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.025247Z"},"links":{"citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:2014bc3047eb7728d6ac74f8ff8cc305bad125ae57b10bc6e90a8e022bdb1e5f","observation_id":"529f0d03-4e79-4f12-ba7d-604136337926","resolution":{"observed_at":"2026-08-12T19:54:20.065820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.03300","last_updated":"2021-01-12T18:57:11Z","snapshot_observed_at":"2026-08-13T20:44:28.824685Z","submitted_at":"2020-09-07T17:59:25Z","title":"Measuring Massive Multitask Language Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.03300","snapshot_observed_at":"2026-08-12T19:54:19.049122Z","title":"Measuring massive multitask language understanding","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.049122Z"},"links":{"cited_paper":"/paper/2009.03300","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:a3315824f7270b9f1b069662046e3628571203d6c0f4af385514a71b51c4258b","observation_id":"55fa256b-e306-464e-945b-b949beb1dc94","resolution":{"observed_at":"2026-08-12T19:54:19.049122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-12T19:54:19.019137Z","title":"Training a helpful and harmless assistant with reinforcement learning from human feedback","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:19.019137Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2411.10242"},"observation_digest":"sha256:bc023f2ce1d6cd967681209d3141667746a317c5e624f8198d630e25df3e2cfb","observation_id":"3dbb4d42-5518-4b8a-81e4-ff664c9dd5bd","resolution":{"observed_at":"2026-08-12T19:54:19.019137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.10242","last_updated":"2024-11-15T14:55:01Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-14T19:16:19.935555Z","submitted_at":"2024-11-15T14:55:01Z","title":"Measuring Non-Adversarial Reproduction of Training Data in Large Language Models"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":1,"verified_fuzzy":12},"total_outbound_references":28},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 3 inbound Pith citation observations for arXiv:2411.10242."}