{"as_of":"2026-08-10T09:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:04a07a47975d4e2ddf42df1b0ccea74912d65d5cf2b21673e7436e974f7b804c","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T06:02:27.958702Z","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":4,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":"2309.10677","doi":"10.48550/arxiv.2309.10677","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2309.10677 , year=","venue":"arXiv (Cornell University)","work_id":"5773f7ab-ba5c-4eef-b27c-dcb64cc33668","year":2023},"citing_paper":{"arxiv_id":"2406.04244","last_updated":"2024-06-06T16:41:39Z","snapshot_observed_at":"2026-07-30T15:43:06.151242Z","submitted_at":"2024-06-06T16:41:39Z","title":"Benchmark Data Contamination of Large Language Models: A Survey","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-22T23:10:40.420241Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2406.04244"},"observation_digest":"sha256:63321cfb123d4893cdee34a0ba6e87980f27e3db7d54c9b2f2601997937d6db2","observation_id":"c820bea0-77f0-4cc3-a4b9-a0b06817bc97","resolution":{"observed_at":"2026-05-22T23:10:41.028002Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-09T18:11:34.992365Z","title":"Estimating contamination via perplexity: Quantifying memorisation in language model evaluation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.00678","last_updated":"2025-05-20T20:47:57Z","snapshot_observed_at":"2026-08-10T03:23:46.877552Z","submitted_at":"2025-02-02T05:50:39Z","title":"How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T18:11:34.992365Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2502.00678"},"observation_digest":"sha256:bb4a6b54ef9998f785db0ef4fc46fed0b240f62194045f6c0ec046af47d65dc4","observation_id":"033cd38c-224c-43f2-9ddd-98674589c3f8","resolution":{"observed_at":"2026-08-09T18:11:34.992365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-07T12:35:26.977795Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.24263","last_updated":"2025-05-30T06:37:39Z","snapshot_observed_at":"2026-08-09T17:21:24.329215Z","submitted_at":"2025-05-30T06:37:39Z","title":"Simulating Training Data Leakage in Multiple-Choice Benchmarks for LLM Evaluation","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T12:35:26.977795Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2505.24263"},"observation_digest":"sha256:119526328a74358580c476c75974b5d213aa93028cec96b6615c8fff17a7f007","observation_id":"3a55477a-f0cc-4719-8e26-4ed2979c2896","resolution":{"observed_at":"2026-08-07T12:35:26.977795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-07T10:54:26.295693Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.04142","last_updated":"2025-06-04T16:33:44Z","snapshot_observed_at":"2026-08-07T21:43:19.257599Z","submitted_at":"2025-06-04T16:33:44Z","title":"Establishing Trustworthy LLM Evaluation via Shortcut Neuron Analysis","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T10:54:26.295693Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2506.04142"},"observation_digest":"sha256:bf03535d8cb57db731333707aed2d0c904a711adbf3aab896e221aee2719220b","observation_id":"86067b5c-a2f2-46c8-b25f-e75f0c369c44","resolution":{"observed_at":"2026-08-07T10:54:26.295693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":"2309.10677","doi":"10.48550/arxiv.2309.10677","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2309.10677 , year=","venue":"arXiv (Cornell University)","work_id":"5773f7ab-ba5c-4eef-b27c-dcb64cc33668","year":2023},"citing_paper":{"arxiv_id":"2605.06327","last_updated":"2026-05-07T14:23:31Z","snapshot_observed_at":"2026-07-06T23:18:51.157048Z","submitted_at":"2026-05-07T14:23:31Z","title":"Measuring Evaluation-Context Divergence in Open-Weight LLMs: A Paired-Prompt Protocol with Pilot Evidence of Alignment-Pipeline-Specific Heterogeneity","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-08T10:23:02.697982Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2605.06327"},"observation_digest":"sha256:3409f96d170a28e399d5180006024385e6b2af969040ee801778b13841845e4c","observation_id":"3a23f700-7fd3-4219-90c1-be9535d467ff","resolution":{"observed_at":"2026-05-08T22:04:18.052583Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":"2309.10677","doi":"10.48550/arxiv.2309.10677","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2309.10677 , year=","venue":"arXiv (Cornell University)","work_id":"5773f7ab-ba5c-4eef-b27c-dcb64cc33668","year":2023},"citing_paper":{"arxiv_id":"2605.07046","last_updated":"2026-05-07T23:52:12Z","snapshot_observed_at":"2026-07-06T23:19:25.538514Z","submitted_at":"2026-05-07T23:52:12Z","title":"An Interpretable and Scalable Framework for Evaluating Large Language Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-11T01:08:25.577363Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2605.07046"},"observation_digest":"sha256:635e12f4022468911615061aea160dca2041f24ffc5e7fb8d0a492eeb5f034b8","observation_id":"5834c8d5-4fd1-4e13-ad15-cccda5b6f6e0","resolution":{"observed_at":"2026-05-11T04:41:01.570612Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":"2309.10677","doi":"10.48550/arxiv.2309.10677","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2309.10677 , year=","venue":"arXiv (Cornell University)","work_id":"5773f7ab-ba5c-4eef-b27c-dcb64cc33668","year":2023},"citing_paper":{"arxiv_id":"2605.21543","last_updated":"2026-05-20T09:16:39Z","snapshot_observed_at":"2026-08-01T19:04:50.092578Z","submitted_at":"2026-05-20T09:16:39Z","title":"Provable Joint Decontamination for Benchmarking Multiple Large Language Models","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-22T00:40:54.038367Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2605.21543"},"observation_digest":"sha256:47d7db817d59a10632e518ec1faf179430a2bc42dfb2c3dd85f0eb36faf40eef","observation_id":"c16934d6-2bc7-45dd-aa53-6b6d19c1c62e","resolution":{"observed_at":"2026-05-22T00:44:29.427759Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":"2309.10677","doi":"10.48550/arxiv.2309.10677","metadata_source":"arxiv_reference","pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2309.10677 , year=","venue":"arXiv (Cornell University)","work_id":"5773f7ab-ba5c-4eef-b27c-dcb64cc33668","year":2023},"citing_paper":{"arxiv_id":"2605.26133","last_updated":"2026-05-21T10:32:33Z","snapshot_observed_at":"2026-08-07T10:44:40.983544Z","submitted_at":"2026-05-21T10:32:33Z","title":"Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-30T17:20:16.735285Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2605.26133"},"observation_digest":"sha256:460b94f7a787d6b6869706ad7c1b627fbd47a5ff27a58632994403556eb0fdb4","observation_id":"f2182f77-fe4c-47f6-b4cb-36b19fd18d4f","resolution":{"observed_at":"2026-06-30T17:24:57.288015Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-07T23:25:20.442787Z","title":"Estimating contamination via perplexity: quantifying memorisation in language model evaluation.URL https://arxiv","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05797","last_updated":"2026-08-06T09:33:09Z","snapshot_observed_at":"2026-08-09T23:11:34.411494Z","submitted_at":"2026-08-06T09:33:09Z","title":"Predicting Task Difficulty Without Rollouts","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T23:25:20.442787Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2608.05797"},"observation_digest":"sha256:cdf9bcff24207dca55fb886db2250adfc6d7e08c0ac45d8b152539d277789dcd","observation_id":"a9a3e6b1-6af2-40f7-8702-d757e1c18d07","resolution":{"observed_at":"2026-08-07T23:25:20.442787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10677","snapshot_observed_at":"2026-08-10T06:02:27.958702Z","title":"Estimating Contamination via Perplexity:","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07341","last_updated":"2026-08-07T15:37:03Z","snapshot_observed_at":"2026-08-10T08:11:55.945084Z","submitted_at":"2026-08-07T15:37:03Z","title":"Zero Gap Is Not Restoration: Stratified Per-Question Probability Evaluation and Step-wise Mitigation of Benchmark Contamination","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-10T06:02:27.958702Z"},"links":{"cited_paper":"/paper/2309.10677","citing_paper":"/paper/2608.07341"},"observation_digest":"sha256:493fde3eb1b3910d53395f7f0702d6e90fe3a3dbbded684e22da4cca86faa650","observation_id":"d04425ab-053e-4ec3-8b66-33e6ea411669","resolution":{"observed_at":"2026-08-10T06:02:27.958702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2309.10677/citation-record","integrity":"/paper/2309.10677/integrity","json":"/paper/2309.10677/citation-record.json","paper":"/paper/2309.10677"},"outbound":[],"paper":{"arxiv_id":"2309.10677","last_updated":"2023-09-27T01:15:49Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T15:02:58Z","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2309.10677."}