{"as_of":"2026-08-09T14:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f05a638d873a3331d64bbd5f38f9e98d790ae42e5da364095d452f926fb2bba0","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":21,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T04:11:59.861601Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":3,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-09T04:11:59.861601Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.03692","last_updated":"2025-02-06T00:58:21Z","snapshot_observed_at":"2026-08-09T04:02:43.782362Z","submitted_at":"2025-02-06T00:58:21Z","title":"DocMIA: Document-Level Membership Inference Attacks against DocVQA Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T04:11:59.861601Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2502.03692"},"observation_digest":"sha256:b1c6fc5fd62baa95832dbf13ef4fa71f642d06399bd13bb245866ce7f115d23c","observation_id":"b20cd380-7302-4846-bcfb-40d6757d1a3e","resolution":{"observed_at":"2026-08-09T04:11:59.861601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-07T15:26:25.147132Z","title":"Zhang, J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15209","last_updated":"2025-05-31T04:26:58Z","snapshot_observed_at":"2026-08-08T00:47:46.009254Z","submitted_at":"2025-05-21T07:37:35Z","title":"DUSK: Do Not Unlearn Shared Knowledge","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T15:26:25.147132Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2505.15209"},"observation_digest":"sha256:5a17623c847b3b8790317282549a72ca3b956231c5c0c72440156cd54add0738","observation_id":"5207c1a4-dda9-4edf-9908-bf130e0cc506","resolution":{"observed_at":"2026-08-07T15:26:25.147132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-07T12:50:06.177607Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03179","last_updated":"2025-05-29T13:17:25Z","snapshot_observed_at":"2026-08-08T00:26:20.360231Z","submitted_at":"2025-05-29T13:17:25Z","title":"Vid-SME: Membership Inference Attacks against Large Video Understanding Models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T12:50:06.177607Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2506.03179"},"observation_digest":"sha256:080349286fd02b4bc423cbd5b136c12e01590ab2ddfb97a144106e132d611b7c","observation_id":"548de2d1-4350-4c21-b212-3e1c67f612a8","resolution":{"observed_at":"2026-08-07T12:50:06.177607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-07T10:27:30.967563Z","title":"Min-k%++: Improved baseline for detecting pre-training data from 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":"2026-08-07T10:21:25.484374Z","submitted_at":"2025-06-05T15:13:57Z","title":"Membership Inference Attacks on Sequence Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T10:27:30.967563Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2506.05126"},"observation_digest":"sha256:148077bfb0d162d5348d691ef15519d4accba4d0cb08fb2d4c48ccf6030302c6","observation_id":"1d64ba19-d40c-4db7-b05e-9791aa2bd424","resolution":{"observed_at":"2026-08-07T10:27:30.967563Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-07T05:41:16.451624Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07399","last_updated":"2025-06-09T03:48:50Z","snapshot_observed_at":"2026-08-09T04:57:01.589232Z","submitted_at":"2025-06-09T03:48:50Z","title":"MrM: Black-Box Membership Inference Attacks against Multimodal RAG Systems","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:16.451624Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2506.07399"},"observation_digest":"sha256:95e48e19450da3f8723dead9a25ffe684087d2d4ee737d616dbdf913867cfd16","observation_id":"54e7395b-2eba-4243-8bec-cb458cf5e60b","resolution":{"observed_at":"2026-08-07T05:41:16.451624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-07T04:33:17.063199Z","title":"Min-k%++: Improved baseline for de- tecting pre-training data from large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.10424","last_updated":"2025-06-12T07:23:56Z","snapshot_observed_at":"2026-08-08T16:23:05.158098Z","submitted_at":"2025-06-12T07:23:56Z","title":"SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-07T04:33:17.063199Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2506.10424"},"observation_digest":"sha256:9407d92d870ff6ba131b076c60f73afc8cf4410e44ec1f32bb026fab5e98dac8","observation_id":"8c09842f-e619-420a-9d09-bbaf013e431f","resolution":{"observed_at":"2026-08-07T04:33:17.063199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-06T15:15:21.428831Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16414","last_updated":"2025-07-22T10:05:30Z","snapshot_observed_at":"2026-08-08T15:54:04.046664Z","submitted_at":"2025-07-22T10:05:30Z","title":"Identifying Pre-training Data in LLMs: A Neuron Activation-Based Detection Framework","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-06T15:15:21.428831Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2507.16414"},"observation_digest":"sha256:b92304e4ef211e7b19a0ff74b6db146a02ef4b3b79af65742e864c7ff6c1a62c","observation_id":"27c22f6c-8553-4cf2-9002-a8896860bd67","resolution":{"observed_at":"2026-08-06T15:15:21.428831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-06T14:51:53.839169Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.17389","last_updated":"2025-07-23T10:34:22Z","snapshot_observed_at":"2026-08-07T11:21:36.520513Z","submitted_at":"2025-07-23T10:34:22Z","title":"Investigating Training Data Detection in AI Coders","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T14:51:53.839169Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2507.17389"},"observation_digest":"sha256:ea102409f6b50aa446b379b73fc17177109511c687f38680f230d8ef2a5cce5a","observation_id":"34c00687-a372-46be-8ae7-bcb5347cb0e3","resolution":{"observed_at":"2026-08-06T14:51:53.839169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T05:29:27.157115Z","title":"F.; and Li, H","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05449","last_updated":"2025-09-05T19:05:49Z","snapshot_observed_at":"2026-08-08T22:19:18.995117Z","submitted_at":"2025-09-05T19:05:49Z","title":"Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-05T05:29:27.157115Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2509.05449"},"observation_digest":"sha256:cf60711196512d41be8c9fc87d28196a2e30906f54dfa82d7206c42f3565661f","observation_id":"034fc69a-6222-4535-ab99-2cf42a1c8c0d","resolution":{"observed_at":"2026-08-05T05:29:27.157115Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-04T11:23:22.454938Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models.arXiv preprint arXiv:2404.02936, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.05699","last_updated":"2026-05-25T05:56:04Z","snapshot_observed_at":"2026-08-09T08:50:47.672362Z","submitted_at":"2025-10-07T09:05:40Z","title":"Membership Inference Attacks on Tokenizers of Large Language Models","version":4},"reference_index":108,"source":"pdf_text","source_observed_at":"2026-08-04T11:23:22.454938Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2510.05699"},"observation_digest":"sha256:8afc8d91c21969105347d9cc92028f98c0936b45faf01417063de5ccf24e15c0","observation_id":"8052ae0b-864b-4d1b-a8ad-db208d0d0cdc","resolution":{"observed_at":"2026-08-04T11:23:22.454938Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-04T07:22:09.311136Z","title":"Min-k URL https://arxiv.org/abs/2404.02936","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.27313","last_updated":"2026-08-02T16:40:30Z","snapshot_observed_at":"2026-08-08T04:38:26.888452Z","submitted_at":"2025-10-31T09:39:12Z","title":"LLM generation novelty through the lens of semantic similarity","version":3},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-04T07:22:09.311136Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2510.27313"},"observation_digest":"sha256:559f9d1d89ca932a2ea5c6c23af19c06415cd2b6ee6f3dbe7d673948bf844fe0","observation_id":"36584a79-e6c1-4784-b819-5ccbfe15c863","resolution":{"observed_at":"2026-08-04T07:22:09.311136Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2511.14045","last_updated":"2026-05-09T12:37:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-18T01:51:34Z","title":"Auditing Data Membership in Reinforcement Learning With Verifiable Rewards","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-17T21:37:54.702010Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2511.14045"},"observation_digest":"sha256:def258fdc5d1caafb0de0d85526761f7ef46f479524aa0f833205254b87d044c","observation_id":"625fbecc-31a9-4d15-8ad8-89a18e076274","resolution":{"observed_at":"2026-05-17T21:40:17.766089Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2512.03121","last_updated":"2026-05-21T10:20:13Z","snapshot_observed_at":"2026-08-06T09:19:02.204242Z","submitted_at":"2025-12-02T14:11:51Z","title":"Lost in Modality: Evaluating the Effectiveness of Text-Based Membership Inference Attacks on Large Multimodal Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-22T11:42:18.076004Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2512.03121"},"observation_digest":"sha256:b34c05c4993f96fd8abe147bda3d3e189f915b11a034c63f43d630be4b9e66b7","observation_id":"ceca5c65-e301-4a5f-a529-51ac3e4385ff","resolution":{"observed_at":"2026-05-22T11:44:50.219620Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2604.03199","last_updated":"2026-04-03T17:17:51Z","snapshot_observed_at":"2026-08-02T10:19:39.008617Z","submitted_at":"2026-04-03T17:17:51Z","title":"Learning the Signature of Memorization in Autoregressive Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-13T19:53:10.396785Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2604.03199"},"observation_digest":"sha256:e4f97c793b2321dec32157768bdfe421f93220662830eb71f31da8a325f5ed89","observation_id":"a7adb287-207d-4551-b810-bc240ae08fef","resolution":{"observed_at":"2026-05-13T19:53:11.478145Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2605.24079","last_updated":"2026-05-22T17:30:20Z","snapshot_observed_at":"2026-08-01T09:58:43.814751Z","submitted_at":"2026-05-22T17:30:20Z","title":"TRACER: A Semantic-Aware Framework for Fine-Grained Contamination Detection in Code LLMs","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-30T15:32:05.976335Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2605.24079"},"observation_digest":"sha256:1f26311504f16e44db06c4348ed5a28278dea29ba79a0e7bd8aef7ca0152e74e","observation_id":"df7fb1b4-698c-4156-b89d-f663c5452565","resolution":{"observed_at":"2026-06-30T15:34:47.938818Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2606.03328","last_updated":"2026-07-30T06:41:18Z","snapshot_observed_at":"2026-08-02T23:18:01.472395Z","submitted_at":"2026-06-02T08:38:14Z","title":"Averaged Evaluation Masks Capability Trade-Offs: Multi-Source Calibration for High-Sparsity LLM Pruning","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-06-28T11:27:02.902720Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2606.03328"},"observation_digest":"sha256:69e518c00f49b489e6756589ff50c842d6f11ceae95b455451f71a50146f227e","observation_id":"00cc933f-07da-414e-b0a8-d626ea453f1b","resolution":{"observed_at":"2026-07-02T01:56:27.596710Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-02T12:32:56.389581Z","title":"Mingjie Sun, Zhuang Liu, Anna Bair, and J Zico Kolter","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.03328","last_updated":"2026-07-30T06:41:18Z","snapshot_observed_at":"2026-08-02T23:18:01.472395Z","submitted_at":"2026-06-02T08:38:14Z","title":"Averaged Evaluation Masks Capability Trade-Offs: Multi-Source Calibration for High-Sparsity LLM Pruning","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T12:32:56.389581Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2606.03328"},"observation_digest":"sha256:573dcbc768af77be2370f99adc0fd834ad614393c21f2033a7be7d136936c7f0","observation_id":"e07449e6-5615-4e5d-830a-d4a80a3db36c","resolution":{"observed_at":"2026-08-02T12:32:56.389581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2606.07996","last_updated":"2026-06-06T06:27:54Z","snapshot_observed_at":"2026-07-31T22:22:12.944552Z","submitted_at":"2026-06-06T06:27:54Z","title":"MC-PDD: Masked Corpus-Level Pretraining Data Detection for Black-Box Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T20:02:50.169589Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2606.07996"},"observation_digest":"sha256:093536c682d5e3050dc23582f4ed588b908116c4e83ce8704b8e2ec845dfca0e","observation_id":"a0c2d51d-8867-4505-9a6a-2d199d838521","resolution":{"observed_at":"2026-07-02T20:57:23.329479Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":"2404.02936","doi":"10.48550/arxiv.2404.02936","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Min-k%++: Improved baseline for detecting pre-training data from large language models","venue":"arXiv (Cornell University)","work_id":"c265805c-ef58-480e-b29b-f3dcaa510aa5","year":2025},"citing_paper":{"arxiv_id":"2606.31991","last_updated":"2026-06-30T17:29:04Z","snapshot_observed_at":"2026-07-07T00:05:37.068846Z","submitted_at":"2026-06-30T17:29:04Z","title":"Amplifying Membership Signal Through Chained Regeneration","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-01T06:22:08.140403Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2606.31991"},"observation_digest":"sha256:2e3e4730939a9ac48f329e6c9c7fc8d7f3dd82bfb7e38b376f461770507e071e","observation_id":"f02e6a18-0bbf-4e9c-b300-0dbdb7bc3c4f","resolution":{"observed_at":"2026-07-01T06:25:26.760412Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-02T02:44:37.193909Z","title":"Min-k large language models, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.14242","last_updated":"2026-07-15T18:03:08Z","snapshot_observed_at":"2026-08-06T07:44:58.399871Z","submitted_at":"2026-07-15T18:03:08Z","title":"Implicit Reasoning Steering via Concept Chaining","version":1},"reference_index":188,"source":"arxiv_source","source_observed_at":"2026-08-02T02:44:37.193909Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2607.14242"},"observation_digest":"sha256:f436ef77c09f5b76ff6a69e91a25f874c6dc5f608aff54d21db052de3aa2b112","observation_id":"3d34a930-1de0-4218-a169-0891cc3ef470","resolution":{"observed_at":"2026-08-02T02:44:37.193909Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02936","snapshot_observed_at":"2026-08-01T00:35:50.513439Z","title":"https: //github.com/tatsu-lab/stanford_alpaca","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27836","last_updated":"2026-07-30T08:15:58Z","snapshot_observed_at":"2026-08-09T07:31:34.339252Z","submitted_at":"2026-07-30T08:15:58Z","title":"Crossing the Margin Cliff: Toward Relearn-Robust LLM Unlearning via Margin Calibration","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T00:35:50.513439Z"},"links":{"cited_paper":"/paper/2404.02936","citing_paper":"/paper/2607.27836"},"observation_digest":"sha256:64aa558d6cf5a8eadc4b785a538013ef930775d7e6bfad8ef5093e332955862c","observation_id":"3c0af4f0-f221-4eca-aa36-a9b188f75ecc","resolution":{"observed_at":"2026-08-01T00:35:50.513439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.02936/citation-record","integrity":"/paper/2404.02936/integrity","json":"/paper/2404.02936/citation-record.json","paper":"/paper/2404.02936"},"outbound":[],"paper":{"arxiv_id":"2404.02936","last_updated":"2025-02-12T04:41:34Z","latest_version":4,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T22:02:50.460833Z","submitted_at":"2024-04-03T04:25:01Z","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2404.02936."}