{"as_of":"2026-08-20T10:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d7cbbf445500c5669fc2933b8f88f7f96a2a90952ba66ad686b359dc6679d969","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T21:12:49.837778Z","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":"2503.11985","last_updated":"2025-05-27T05:40:29Z","snapshot_observed_at":"2026-08-17T15:57:48.716950Z","submitted_at":"2025-03-15T03:58:14Z","title":"No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models","version":2},"cited_work":{"arxiv_id":"2503.11985","doi":"10.48550/arxiv.2503.11985","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.11985","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"No llm is free from bias: A com- prehensive study of bias evaluation in large lan- guage models.arXiv preprint arXiv:2503.11985","venue":"arXiv (Cornell University)","work_id":"39abb979-91e6-4d1d-82d4-f69658306bf7","year":2018},"citing_paper":{"arxiv_id":"2511.11030","last_updated":"2026-04-15T13:49:28Z","snapshot_observed_at":"2026-07-06T22:35:46.018050Z","submitted_at":"2025-11-14T07:34:29Z","title":"Algorithms Trained on Normal Chest X-rays Can Predict Health Insurance Types","version":6},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-17T22:34:52.896200Z"},"links":{"cited_paper":"/paper/2503.11985","citing_paper":"/paper/2511.11030"},"observation_digest":"sha256:d7382aab9e716b829ac7f692fbdcb33ede16bd598910823f3f939a00d0ab1e8d","observation_id":"c7231fc4-ba49-4d57-8019-81550b3f9b27","resolution":{"observed_at":"2026-05-17T22:35:25.036271Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11985","last_updated":"2025-05-27T05:40:29Z","snapshot_observed_at":"2026-08-17T15:57:48.716950Z","submitted_at":"2025-03-15T03:58:14Z","title":"No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models","version":2},"cited_work":{"arxiv_id":"2503.11985","doi":"10.48550/arxiv.2503.11985","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.11985","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"No llm is free from bias: A com- prehensive study of bias evaluation in large lan- guage models.arXiv preprint arXiv:2503.11985","venue":"arXiv (Cornell University)","work_id":"39abb979-91e6-4d1d-82d4-f69658306bf7","year":2018},"citing_paper":{"arxiv_id":"2606.12422","last_updated":"2026-05-08T16:32:43Z","snapshot_observed_at":"2026-08-19T04:19:57.254608Z","submitted_at":"2026-05-08T16:32:43Z","title":"Creating and Evaluating K-12 GenAI Assessment Graders Through Context Engineering","version":1},"reference_index":230,"source":"arxiv_source","source_observed_at":"2026-06-30T22:54:03.054871Z"},"links":{"cited_paper":"/paper/2503.11985","citing_paper":"/paper/2606.12422"},"observation_digest":"sha256:4c545a76682dfeaae5f18680c2a1907ecc09ee718a6f3a5cd49db66920c2c0b7","observation_id":"8284a470-7075-4d65-9c76-973cc28f8bb9","resolution":{"observed_at":"2026-06-30T22:55:06.200993Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11985","last_updated":"2025-05-27T05:40:29Z","snapshot_observed_at":"2026-08-17T15:57:48.716950Z","submitted_at":"2025-03-15T03:58:14Z","title":"No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models","version":2},"cited_work":{"arxiv_id":"2503.11985","doi":"10.48550/arxiv.2503.11985","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.11985","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"No llm is free from bias: A com- prehensive study of bias evaluation in large lan- guage models.arXiv preprint arXiv:2503.11985","venue":"arXiv (Cornell University)","work_id":"39abb979-91e6-4d1d-82d4-f69658306bf7","year":2018},"citing_paper":{"arxiv_id":"2606.17506","last_updated":"2026-06-16T04:28:56Z","snapshot_observed_at":"2026-08-17T17:52:59.133755Z","submitted_at":"2026-06-16T04:28:56Z","title":"Evaluating Second-Order Bias of LLMs Through Epistemic Entitlement","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T01:24:55.378559Z"},"links":{"cited_paper":"/paper/2503.11985","citing_paper":"/paper/2606.17506"},"observation_digest":"sha256:6abb60451735ecca3f023c4595b07fb9c9fb8e00d1e12cfb936232b10e62e09a","observation_id":"cdc8326d-12db-4c3e-b3de-063f68bdebf5","resolution":{"observed_at":"2026-07-03T20:18:57.359099Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11985","last_updated":"2025-05-27T05:40:29Z","snapshot_observed_at":"2026-08-17T15:57:48.716950Z","submitted_at":"2025-03-15T03:58:14Z","title":"No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11985","snapshot_observed_at":"2026-08-15T21:12:49.837778Z","title":"arXiv preprint arXiv:2503.11985 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.12894","last_updated":"2026-08-13T07:23:53Z","snapshot_observed_at":"2026-08-19T06:11:25.484941Z","submitted_at":"2026-08-13T07:23:53Z","title":"BavGround: A Benchmark for Regional Cultural Grounding and Dialect Competence in Bavarian","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-15T21:12:49.837778Z"},"links":{"cited_paper":"/paper/2503.11985","citing_paper":"/paper/2608.12894"},"observation_digest":"sha256:be9af9a24d936582563a4e480d9e8c4809304012809d796a9582d542c54a9da4","observation_id":"6327cdce-5e37-4c63-9f13-7e55e684eb7d","resolution":{"observed_at":"2026-08-15T21:12:49.837778Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.11985/citation-record","integrity":"/paper/2503.11985/integrity","json":"/paper/2503.11985/citation-record.json","paper":"/paper/2503.11985"},"outbound":[],"paper":{"arxiv_id":"2503.11985","last_updated":"2025-05-27T05:40:29Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-17T15:57:48.716950Z","submitted_at":"2025-03-15T03:58:14Z","title":"No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in 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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.11985."}