{"as_of":"2026-08-08T22:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:295ce1b6c89e7a49e6db9c1348e68a6effaa66f599a9224561792742da31ee4a","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:21:36.988483Z","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":"2026-06-29T07:33:13.390618Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-08-07T14:21:36.988483Z","title":"The vulnerability of language model benchmarks: Do they accurately reflect true llm performance? arXiv preprint arXiv:2412.03597, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23790","last_updated":"2025-05-25T22:31:24Z","snapshot_observed_at":"2026-08-07T14:13:52.832188Z","submitted_at":"2025-05-25T22:31:24Z","title":"Rethinking the Understanding Ability across LLMs through Mutual Information","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:21:36.988483Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2505.23790"},"observation_digest":"sha256:3e5f5e235098d968bea8de813841d7d813d4226c544d95fcf8d8e2f8fad7e451","observation_id":"6a78e576-5327-4cb2-abe6-488df5659def","resolution":{"observed_at":"2026-08-07T14:21:36.988483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2508.05452","last_updated":"2026-04-15T14:48:07Z","snapshot_observed_at":"2026-07-06T22:09:28.204393Z","submitted_at":"2025-08-07T14:46:30Z","title":"LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models","version":7},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-19T00:39:02.015913Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2508.05452"},"observation_digest":"sha256:c0396279bcca292452c9ce678bc7275cdbf4c49fc6495582e5aad2173d3ec863","observation_id":"4bd3f3c2-d3b9-4673-bab5-53e4d143ff46","resolution":{"observed_at":"2026-05-19T00:41:55.997298Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2509.23023","last_updated":"2026-05-14T13:52:45Z","snapshot_observed_at":"2026-08-03T02:05:46.573077Z","submitted_at":"2025-09-27T00:40:19Z","title":"Deceive, Detect, and Disclose: Large Language Models Play Mini-Mafia","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-18T13:25:17.313704Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2509.23023"},"observation_digest":"sha256:700ba145b8f0dccb72c5d5838f69f665cfe9e1771391462decb036acfc376900","observation_id":"027116f9-b917-4296-870b-6cba7ef60d16","resolution":{"observed_at":"2026-05-18T13:26:24.835532Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2510.06989","last_updated":"2026-04-15T08:06:12Z","snapshot_observed_at":"2026-08-05T11:44:17.049904Z","submitted_at":"2025-10-08T13:13:18Z","title":"Human-aligned AI Model Cards with Weighted Hierarchy Architecture","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-18T09:09:11.154051Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2510.06989"},"observation_digest":"sha256:2b35128847bcf655e42827539115fd6308619b9fdfff975eaeb312b0bc22a975","observation_id":"3680f679-e001-4f0e-bc07-05f693db9aae","resolution":{"observed_at":"2026-05-18T09:11:09.673896Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2604.13371","last_updated":"2026-04-15T00:35:22Z","snapshot_observed_at":"2026-08-08T12:23:50.044941Z","submitted_at":"2026-04-15T00:35:22Z","title":"Empirical Evidence of Complexity-Induced Limits in Large Language Models on Finite Discrete State-Space Problems with Explicit Validity Constraints","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-05-10T14:12:45.438246Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2604.13371"},"observation_digest":"sha256:020a4a5ecf0d04a04ce67269cd5ba682a1cbd7edc78b47f668e3311f9386fc55","observation_id":"cd72ad2b-5c21-4586-ba94-6a6d7070fc1a","resolution":{"observed_at":"2026-05-10T14:15:29.437860Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2604.23067","last_updated":"2026-04-24T23:37:17Z","snapshot_observed_at":"2026-08-02T12:00:10.017635Z","submitted_at":"2026-04-24T23:37:17Z","title":"Training a General Purpose Automated Red Teaming Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T11:20:09.224745Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2604.23067"},"observation_digest":"sha256:dc9898200ee7347afaf0fa7febd7d29ce15b95b92ef23c75fbe26a179c42375c","observation_id":"20ac7aa0-9ded-4b97-a1af-337206e4eebe","resolution":{"observed_at":"2026-05-11T19:41:08.329246Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":"2412.03597","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-06-29T07:33:13.390618Z","title":"Chang, Y .; Wang, X.; Wang, J.; Wu, Y .; Zhu, K.; Chen, H.; Yang, L.; Yi, X.; Wang, C.; Wang, Y .; Ye, W.; Zhang, Y .; Chang, Y .; Yu, P","venue":null,"work_id":"03c6e28a-3346-480e-b56f-3c5165800ae9","year":2024},"citing_paper":{"arxiv_id":"2605.30018","last_updated":"2026-05-29T04:32:57Z","snapshot_observed_at":"2026-07-06T23:39:20.085961Z","submitted_at":"2026-05-28T14:41:26Z","title":"Latent Performance Profiling of Large Language Models","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-06-29T07:31:02.595386Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2605.30018"},"observation_digest":"sha256:f33dcf14156e523987ff30095da0b5554d2934afb3dc73eeb188146380f1e8a7","observation_id":"bd84c14f-df89-4b4d-9160-73d8af3b0f08","resolution":{"observed_at":"2026-06-29T07:33:13.392079Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03597","snapshot_observed_at":"2026-08-07T12:44:35.307850Z","title":"arXiv preprint arXiv:2412.03597 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.06202","last_updated":"2026-08-06T15:58:32Z","snapshot_observed_at":"2026-08-08T22:19:03.390311Z","submitted_at":"2026-08-06T15:58:32Z","title":"What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations)","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:35.307850Z"},"links":{"cited_paper":"/paper/2412.03597","citing_paper":"/paper/2608.06202"},"observation_digest":"sha256:ef334aaa902d302fb958cbc72f0f779995f83f21f0417459d55afa39d42e4fd4","observation_id":"7bcf96d0-68e2-4d3c-b056-ed6c588043bb","resolution":{"observed_at":"2026-08-07T12:44:35.307850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.03597/citation-record","integrity":"/paper/2412.03597/integrity","json":"/paper/2412.03597/citation-record.json","paper":"/paper/2412.03597"},"outbound":[],"paper":{"arxiv_id":"2412.03597","last_updated":"2024-12-02T20:49:21Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-05T12:03:49.244891Z","submitted_at":"2024-12-02T20:49:21Z","title":"The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2412.03597."}