{"as_of":"2026-08-12T13:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:22d3f4021a571410f2e79f4609ecae2286fa8435cd1cf0a5d73d9cebd64ea8b8","coverage":[{"denominator":83,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":83,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:44:09.237881Z","state":"measured"},{"denominator":84,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":84,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-09T23:44:08.610255Z","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":"2026-05-11T14:01:06.694928Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"cited_work":{"arxiv_id":"2505.23996","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.23996","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Xuyang Wu, Jinming Nian, Ting-Ruen Wei, Zhiqiang Tao, Hsin-Tai Wu, and Yi Fang","venue":null,"work_id":"8a2c1fd3-8d0d-4c6e-9ed1-75c30001c47b","year":2025},"citing_paper":{"arxiv_id":"2604.20677","last_updated":"2026-04-23T01:37:34Z","snapshot_observed_at":"2026-08-09T22:08:46.808706Z","submitted_at":"2026-04-22T15:25:47Z","title":"Intersectional Fairness in Large Language Models","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-09T23:44:08.610255Z"},"links":{"cited_paper":"/paper/2505.23996","citing_paper":"/paper/2604.20677"},"observation_digest":"sha256:397f6e4e39353fc59bb7b1c05a455bfb7e65408a60c537c0d3b95252a8dddf6e","observation_id":"d0b62ad9-d922-4ad0-984c-6955fa824d9b","resolution":{"observed_at":"2026-05-11T14:01:06.699849Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.23996/citation-record","integrity":"/paper/2505.23996/integrity","json":"/paper/2505.23996/citation-record.json","paper":"/paper/2505.23996"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.16867","last_updated":"2023-11-29T19:45:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-28T15:12:47Z","title":"The Falcon Series of Open Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.16867","snapshot_observed_at":"2026-08-07T12:44:03.211772Z","title":"The falcon series of open language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.211772Z"},"links":{"cited_paper":"/paper/2311.16867","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:878f5c3aaf614a2ddda62f4416e0d27572c527f82e87ef26fc3a0ec67c894c7e","observation_id":"267a49f6-fb9a-4a7f-8ff7-54ad008f1d7b","resolution":{"observed_at":"2026-08-07T12:44:03.211772Z","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":"2026-08-07T12:44:03.252351Z","title":"The silicon ceiling: Auditing gpt’s race and gender biases in hiring","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.252351Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:4831f63559ecd9b0656c2a9218cd342d067d785085f3e4f53239dd972ff32094","observation_id":"f17bdf98-f59c-4e2f-9c49-ffbfc88517b7","resolution":{"observed_at":"2026-08-07T12:44:03.252351Z","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":"2026-08-07T12:44:03.318792Z","title":"V., and Pan, R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.318792Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:71a8b3e31ec78dc64b9b4e3d693cd04ed55d2c7f40999ae561bd5d4a8dcf9a3b","observation_id":"eb20950c-fb41-464c-be82-10f0ad4cef28","resolution":{"observed_at":"2026-08-07T12:44:03.318792Z","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":"2026-08-07T12:44:03.379829Z","title":"G., Bradley, H., O'Brien, K., Hallahan, E., Khan, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.379829Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:0a373a15c143369432f3d5e5c3a95aabc1b9d6c632b7a79252facf88bc055816","observation_id":"9a1bf20c-610a-4515-838d-db79a3dcbf91","resolution":{"observed_at":"2026-08-07T12:44:03.379829Z","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":"2026-08-07T12:44:18.514924Z","title":"Beyond the imitation game: Quantifying and extrapolating the capabilities of language models","venue":null,"work_id":"3c331a43-3992-47a9-b969-0c1d7c01d747","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.429252Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:575ea06c2e45740e73f5460892dfb379e761e9e27c12ca1db8b1b95e5790e9af","observation_id":"4b8f3a54-d4cd-4adf-8275-7224b04596e9","resolution":{"observed_at":"2026-08-07T12:44:18.568953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:18.403392Z","title":"L., Barocas, S., Daum \\'e III, H., and Wallach, H","venue":null,"work_id":"51e5afd1-436c-4b80-aaa9-b038b8764e09","year":2020},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.498718Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:1e522d5e73c08be90708656fa4340ae1df6ed611e2cbf2cd5788b317d268bb31","observation_id":"d5d09ab7-b3de-4c76-8b34-3051c1fea543","resolution":{"observed_at":"2026-08-07T12:44:18.446346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-07T12:44:03.586468Z","title":"A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.586468Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:a0b3d083180646e1a8f0f85b1b4577073e9dbce561587fb9ee8a3ef03272c3f2","observation_id":"b195c183-f0c0-4945-8f7a-97224aa9f811","resolution":{"observed_at":"2026-08-07T12:44:03.586468Z","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":"2026-08-07T12:44:18.208112Z","title":null,"venue":null,"work_id":"3dc655ae-2561-4c59-9dbc-69bd4a4ab6c7","year":1990},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.679608Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:0a24f2a15125caa53a41096c69e4c5a8939f4aecbe65037c13ca007ae3aefc7f","observation_id":"8d7fc5fa-e812-4860-ae4a-bd43d223fb7b","resolution":{"observed_at":"2026-08-07T12:44:18.269199Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:18.046830Z","title":"Fairness in large language models: A taxonomic survey","venue":null,"work_id":"70401f8a-d371-486c-a117-f03700a7e4a4","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.765386Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:3c22ab730951d022a7c4e71be2eca76c1e632b371c728028621b06e2ffc29675","observation_id":"2d2c9879-b12e-406b-95fe-d252144209f3","resolution":{"observed_at":"2026-08-07T12:44:18.121535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:17.894942Z","title":"Rainproof: An umbrella to shield text generators from out-of-distribution data","venue":null,"work_id":"bb381b91-265b-4d8d-8728-b6722e1e40e7","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.882239Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:9364c974c10ae39f1249c4912bab5d0e8eba9326a046b212bd86d8beda650929","observation_id":"44a6f248-865d-4c73-8c3c-e7ab85da8878","resolution":{"observed_at":"2026-08-07T12:44:17.967413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:03.975683Z","title":"Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:03.975683Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:01bfc0b65cff20be3e7077889bb0112f0b4b2561a884c75021cbc310695e8412","observation_id":"197f1aa5-235c-42b4-bf9a-9d1b97938dbc","resolution":{"observed_at":"2026-08-07T12:44:03.975683Z","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":"2026-08-07T12:44:17.721696Z","title":"Bold: Dataset and metrics for measuring biases in open-ended language generation","venue":null,"work_id":"56d55fb1-81e1-4482-b46c-b6a52ec4ce13","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.025627Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:55667f44883633906af6bd1fc0baba8eeaa38252de26090d7b976a36d4cf9cc7","observation_id":"d8a18180-b3b2-4b2b-ac12-3e0bbf980a4d","resolution":{"observed_at":"2026-08-07T12:44:17.801829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:17.552746Z","title":"Shifting attention to relevance: Towards the uncertainty estimation of large language models","venue":null,"work_id":"d537ba08-6ebf-40da-842c-6b29ddb1527f","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.070551Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:4c33f68a16ae0404d93340a0bfd94afb24b66af17bd28efeb4d50a84c1eb3b82","observation_id":"a16b8b19-898a-4a4e-9333-0e75f14cea62","resolution":{"observed_at":"2026-08-07T12:44:17.605590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-10T16:40:37.411115Z","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":"2026-08-07T12:44:04.134653Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.134653Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:383d0d75a4ab5b7b35ba54f3b9ff2f1b8a97738e781f3d96377a421632d95180","observation_id":"f07540c8-3e8c-4d6b-b6d7-1b7c067214f3","resolution":{"observed_at":"2026-08-07T12:44:04.134653Z","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":"2026-08-07T12:44:17.410420Z","title":"Is your classifier actually biased? measuring fairness under uncertainty with bernstein bounds","venue":null,"work_id":"3488b831-dec4-4b25-8166-72385b5e5cd5","year":2020},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.181777Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:3f57e6fa12dcd3642788f633196583c33573899c9ad3bc5d51a22ac855433ccc","observation_id":"067edf46-7318-4a8c-a34c-f1ebd2cb8b8d","resolution":{"observed_at":"2026-08-07T12:44:17.467523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:17.275323Z","title":null,"venue":null,"work_id":"676bb5d4-16df-4344-b1dd-81c33fb9b69e","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.225529Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:2ccf9d4544db94a9591b382b5f2b7cd5dd8c77494c0bed266bf5641e0c69f46a","observation_id":"b981a3ba-738f-453c-a0e2-c54a7ddaecba","resolution":{"observed_at":"2026-08-07T12:44:17.356648Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:17.140864Z","title":"Lm-polygraph: Uncertainty estimation for language models","venue":null,"work_id":"34ce7dca-8d5a-4c00-b17a-6fd165ef1fbb","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.262182Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:31c097de0d60933a68501b9a38883ba4e0f0d51137b85581c1f58a52339da7d3","observation_id":"a794e728-b1be-47e0-8d0c-00adb3cca5db","resolution":{"observed_at":"2026-08-07T12:44:17.221006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:17.038760Z","title":"L., Waseem, Z., and Tsvetkov, Y","venue":null,"work_id":"8c20dd80-4fe8-4c7a-91eb-794fc97808a1","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.335390Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:c51e4047a6614dd0f22d2743a95715950ccd81cbbdebed24313b15619a137147","observation_id":"04560253-639a-45fa-ab1e-20c325ac77d3","resolution":{"observed_at":"2026-08-07T12:44:17.086920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:16.867079Z","title":"Unsupervised quality estimation for neural machine translation","venue":null,"work_id":"ad8221e5-f1ef-4620-a1e4-54a4b6182556","year":2020},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.442745Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:4c30a60c608679abd13f62f77a54168f8295b2566649547bdde28b046065f9ff","observation_id":"5881bbfb-1859-4960-9fc5-00c566e5f496","resolution":{"observed_at":"2026-08-07T12:44:16.952392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:16.695174Z","title":"Open llm leaderboard v2, 2024","venue":null,"work_id":"8b469875-158c-4033-95e7-b97b8cd073df","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.531740Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:681b18cbbf8180209c788f2f8ecafa67d2946d3d1a3f49833fce94b9ec1822c0","observation_id":"a3ca57aa-9d39-4835-8383-bc20007013fd","resolution":{"observed_at":"2026-08-07T12:44:16.786903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:16.505819Z","title":"and Ghahramani, Z","venue":null,"work_id":"eb38d2ae-c431-4279-b927-27b674fde28b","year":2016},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.597528Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:8fabc141788dc7b5c41e0d96176b64b85004fc0f9c9cc71ed807bc66ba8746ba","observation_id":"f176d5fa-749e-4836-8818-8de98a33160b","resolution":{"observed_at":"2026-08-07T12:44:16.563970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:16.318644Z","title":"O., Rossi, R","venue":null,"work_id":"544d8d73-26d0-4916-979e-efe5bd45db48","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.626150Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:a9a6e9c020eeba506d41fd351e05d67ea52bc2385484756ef1895456b3272413","observation_id":"c804cfaa-d7d0-40c4-938a-ff588d4394ae","resolution":{"observed_at":"2026-08-07T12:44:16.417568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:16.094487Z","title":null,"venue":null,"work_id":"f8b28fc6-5dbc-47c4-8216-67db9352b331","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.700794Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:51c285fc0ad07c4f0fa87c63a2d2cb0f98f6d9514776084765d0c5c437b2d466","observation_id":"4ce52675-f329-481b-9b0c-dff3288e3bb1","resolution":{"observed_at":"2026-08-07T12:44:16.234860Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:15.904876Z","title":"Uncertainty-guided optimization on large language model search trees","venue":null,"work_id":"f57b3404-fdec-49d7-a6d1-4c64b89c167c","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.742444Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:1ddb1e72647b494863ce960c5ea4f13575b1b86291171e0a0582002bb85e2696","observation_id":"6c0d3603-88ef-4ded-8690-bb0e48704e43","resolution":{"observed_at":"2026-08-07T12:44:15.975896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04190","last_updated":"2024-03-07T03:38:44Z","snapshot_observed_at":"2026-08-12T07:41:38.803268Z","submitted_at":"2024-03-07T03:38:44Z","title":"Generative AI for Synthetic Data Generation: Methods, Challenges and the Future","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04190","snapshot_observed_at":"2026-08-07T12:44:04.783265Z","title":"and Chen, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.783265Z"},"links":{"cited_paper":"/paper/2403.04190","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:070cd05a9312607f40cef6f1cd92b5d8202df82acb34dccd11e22e8ca089789d","observation_id":"845b542b-fc39-4034-8828-2eb489d7e20c","resolution":{"observed_at":"2026-08-07T12:44:04.783265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.10915","last_updated":"2026-05-01T02:07:46Z","snapshot_observed_at":"2026-07-06T19:51:28.494860Z","submitted_at":"2024-11-16T23:54:53Z","title":"Bias in Large Language Models: Origin, Evaluation, and Mitigation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.10915","snapshot_observed_at":"2026-08-07T12:44:04.836197Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.836197Z"},"links":{"cited_paper":"/paper/2411.10915","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:be3f7e4728ffa198c587a300feab3e35d123cb477fa1fa76061b147df015b3ff","observation_id":"aa724e5d-ae6b-46b6-a2ee-261700e5d125","resolution":{"observed_at":"2026-08-07T12:44:04.836197Z","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":"2026-08-07T12:44:15.756448Z","title":"Equality of opportunity in supervised learning","venue":null,"work_id":"49118fd8-3c06-487b-a54f-aa6644545a3d","year":2016},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.875490Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:24f26d5bf607b321e363c4e8a16823fb2afce01f075d8fe93290889a11b84b02","observation_id":"c29870cf-afb8-4327-af8b-e4cde30753af","resolution":{"observed_at":"2026-08-07T12:44:15.828040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:15.683846Z","title":"Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection","venue":null,"work_id":"52ba0ec3-93a6-4f85-b68a-ebc00b829689","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.906843Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:1661e012138e934e2c97a98f1c9426d21f60a0f8b6fb9ed0641e6b3b09738fbf","observation_id":"0cb4e436-10e8-4b55-acc3-40da88540576","resolution":{"observed_at":"2026-08-07T12:44:15.726090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:04.987792Z","title":"and Gimpel, K","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:04.987792Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:a7eefef77e86b6f946ffde0f7b86080fa4f216dd50507e012451c817c60e6740","observation_id":"fa5f142f-928c-4395-8bff-bf0e042a8f6c","resolution":{"observed_at":"2026-08-07T12:44:04.987792Z","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":"2026-08-07T12:44:05.064663Z","title":"Measuring massive multitask language understanding","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.064663Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:3747cba73e3c0855e1f57dbd929c64ec685b65721d2088f20831e71035c78008","observation_id":"f06b45b9-9eb0-4ac7-954f-d7a6bddfdfb3","resolution":{"observed_at":"2026-08-07T12:44:05.064663Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.04459","last_updated":"2023-06-05T06:46:53Z","snapshot_observed_at":"2026-07-06T15:39:45.449997Z","submitted_at":"2023-06-05T06:46:53Z","title":"Uncertainty in Natural Language Processing: Sources, Quantification, and Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.04459","snapshot_observed_at":"2026-08-07T12:44:05.127538Z","title":"Uncertainty in natural language processing: Sources, quantification, and applications","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.127538Z"},"links":{"cited_paper":"/paper/2306.04459","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:7191d83aadefb3e841dc04ed313f2d7ad4cf36f0ad2a056a0eff82dd0918d2e2","observation_id":"4ba409ec-371a-40b2-88fa-dabdb7518bb9","resolution":{"observed_at":"2026-08-07T12:44:05.127538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10236","last_updated":"2025-01-05T06:15:04Z","snapshot_observed_at":"2026-08-10T02:33:11.935041Z","submitted_at":"2023-07-16T08:28:04Z","title":"Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10236","snapshot_observed_at":"2026-08-07T12:44:05.183520Z","title":"Look before you leap: An exploratory study of uncertainty measurement for large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.183520Z"},"links":{"cited_paper":"/paper/2307.10236","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:8dc4b7e38c6d2689288cde5e7c2dcf1a5a12a8eadef66cc32048bda8b47fa112","observation_id":"17d49396-5d55-4116-ab29-06355a8eb962","resolution":{"observed_at":"2026-08-07T12:44:05.183520Z","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":"2026-08-07T12:44:15.562245Z","title":"L., Bahl, L","venue":null,"work_id":"32a7a0e0-c230-4f10-8cab-e33d27746c4a","year":1977},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.227274Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:6b5e3cd82b75d9770967c6bb7bf0070724608b828627281f7be8ff3a4e49b0f6","observation_id":"ab931db8-d725-4743-bc0b-4892c070c473","resolution":{"observed_at":"2026-08-07T12:44:15.611090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-07T12:44:05.361003Z","title":"Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.361003Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:c6008d9c0723f1d5d88971c1d2f65c7d79bbed47ebb95938dcd3784d102f4845","observation_id":"6d655d69-9704-4d5c-b42e-01dd3f4d9694","resolution":{"observed_at":"2026-08-07T12:44:05.361003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-08-08T06:16:25.839566Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-07T12:44:05.455604Z","title":"Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.455604Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:79a9d14fc3129132941298b5034167372438bfe7c27a32d2c21fb430b4f1fae8","observation_id":"5026a8ab-faef-402c-a3e4-f089bc9f34b3","resolution":{"observed_at":"2026-08-07T12:44:05.455604Z","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":"2026-08-07T12:44:15.411778Z","title":"and Martin, J","venue":null,"work_id":"bc06dd60-1395-4766-a305-f8de72f435b5","year":2000},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.547422Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:6b934acd20c7362f96410781451b3bc34222736936b7621d6c52c16a904e6ba1","observation_id":"be4ed6db-eb0d-4b7c-b080-f07afa408ef9","resolution":{"observed_at":"2026-08-07T12:44:15.479941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05221","last_updated":"2022-11-21T16:38:35Z","snapshot_observed_at":"2026-08-06T08:34:11.887259Z","submitted_at":"2022-07-11T22:59:39Z","title":"Language Models (Mostly) Know What They Know","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.05221","snapshot_observed_at":"2026-08-07T12:44:05.646636Z","title":"Language models (mostly) know what they know","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.646636Z"},"links":{"cited_paper":"/paper/2207.05221","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:7ae69df8a29f47d5ae24ae1bc83b7ce5eb18e800d85c14bb78e3d0a27c3ae23f","observation_id":"cd954028-4c08-49ae-b3df-ff35f7ba38e8","resolution":{"observed_at":"2026-08-07T12:44:05.646636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.02730","last_updated":"2022-11-04T20:04:39Z","snapshot_observed_at":"2026-08-10T16:01:23.191751Z","submitted_at":"2022-11-04T20:04:39Z","title":"Uncertainty-aware predictive modeling for fair data-driven decisions","version":1},"cited_work":{"arxiv_id":"2211.02730","doi":null,"metadata_source":"pith","pith_arxiv_id":"2211.02730","snapshot_observed_at":"2026-08-07T12:44:10.116382Z","title":"Uncertainty-aware predictive modeling for fair data-driven decisions","venue":"stat.ML","work_id":"a827b14c-4102-41f2-a036-dec81916ebf1","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.735181Z"},"links":{"cited_paper":"/paper/2211.02730","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:9c92e3e26e078ce740add88c561bae53c75f79114bc325b84a598a2c6c1a6b48","observation_id":"098ebb9d-4ddc-4ad3-a6ea-73ff101743dc","resolution":{"observed_at":"2026-08-07T12:44:10.238901Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:15.257773Z","title":"and Gal, Y","venue":null,"work_id":"06fbab44-9b34-465e-9f16-837642164088","year":2017},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.784646Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:8462f45baedd5b219c8e9ca9277b4c56a40a264a13525f7ec0e76b0522827ea9","observation_id":"5f6f6416-8501-4c75-b20c-5f5ead7559e8","resolution":{"observed_at":"2026-08-07T12:44:15.328117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:15.195026Z","title":"Gender bias and stereotypes in large language models","venue":null,"work_id":"db2ea69b-1e04-42f7-8f26-49b1e773c2b3","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.828207Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:27a039d1d20ef43737fee09887bdfa838dc72716f9c20062e6cf44664a9a0458","observation_id":"9260af03-bf8b-4553-8ec1-c82917700bb1","resolution":{"observed_at":"2026-08-07T12:44:15.221107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:15.134641Z","title":"Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation","venue":null,"work_id":"cafd8b7b-084d-4dee-8541-e43781ccea01","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.902880Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:d8066215a49176fd3fcd271a5afb5e485c3bf608be5f97b22550767dc6511035","observation_id":"798933d2-53db-4aee-ae2e-d36e294ceed5","resolution":{"observed_at":"2026-08-07T12:44:15.160020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.ijcnlp-main.48","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Uncertainty estimation for debiased models: Does fairness hurt reliability? In Park, J","venue":null,"work_id":"62e3f68b-96f6-49a8-af97-5a9a497e317a","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:05.969084Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:7eb0d26558adc361dd1a564b9b8776f6e7346c41e6fadc5a383f9fbeace592e8","observation_id":"fdff9ccf-e8c2-41ad-91ab-5c9b3c8074de","resolution":{"observed_at":"2026-08-07T12:44:15.059129Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11299","last_updated":"2024-08-29T08:14:31Z","snapshot_observed_at":"2026-08-10T09:08:34.701157Z","submitted_at":"2023-12-18T15:49:03Z","title":"Uncertainty-based Fairness Measures","version":2},"cited_work":{"arxiv_id":"2312.11299","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.11299","snapshot_observed_at":"2026-08-07T12:44:09.776516Z","title":"Uncertainty-based Fairness Measures","venue":"cs.LG","work_id":"54219896-e465-4004-9de6-a9cae194dc1c","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.027478Z"},"links":{"cited_paper":"/paper/2312.11299","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:deecab87af9627b78a11d5207a1a9f296dceb0c1ac2350db2a996c77455ae424","observation_id":"333277ac-5c58-449b-97f1-7b9c071e17df","resolution":{"observed_at":"2026-08-07T12:44:09.941465Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:14.854973Z","title":null,"venue":null,"work_id":"205491ef-3e15-425d-8555-d3c38cc66455","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.092077Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:80283f811d1196b776bc84ce505b02b83b773793285196fa484e954cb3c04858","observation_id":"12e0d74e-0604-4339-b08c-7b1af3110f49","resolution":{"observed_at":"2026-08-07T12:44:14.929638Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:14.674156Z","title":"End-to-end neural coreference resolution","venue":null,"work_id":"18c1b8db-90a5-4cf8-a364-e5b6a2074e29","year":2017},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.156859Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:e66c013a9404739f39ab45e989e6eda42ad0fcff47f10a10b93e4d593cf9cfbe","observation_id":"f14adab0-3a8c-4588-b257-f1976c23c350","resolution":{"observed_at":"2026-08-07T12:44:14.769524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:14.407164Z","title":"The winograd schema challenge","venue":null,"work_id":"abf229b9-1bd9-428a-90b4-de6197c24fd6","year":2012},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.214632Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:4d1f8426a58e3cd2760513987edc55d214dfdddbcbfefde6ab22cc30ac948191","observation_id":"c0bb72c7-a3bc-4e41-b42e-5616ada4bd59","resolution":{"observed_at":"2026-08-07T12:44:14.540624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:14.164506Z","title":"Collecting a large-scale gender bias dataset for coreference resolution and machine translation","venue":null,"work_id":"53f45cf7-b4c6-4dc0-9de2-c2d1226855cf","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.302999Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:736577eba5c88260917beae4d366a6694abcddbe776f0853d43d6f740aa18399","observation_id":"361ca2d0-a944-429a-8d08-d7541daf1106","resolution":{"observed_at":"2026-08-07T12:44:14.275121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10149","last_updated":"2024-02-21T13:52:11Z","snapshot_observed_at":"2026-08-08T00:38:29.757258Z","submitted_at":"2023-08-20T03:30:22Z","title":"A Survey on Fairness in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.10149","snapshot_observed_at":"2026-08-07T12:44:06.379726Z","title":"A survey on fairness in large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.379726Z"},"links":{"cited_paper":"/paper/2308.10149","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:681005801936723e8f3e0337f7089a7bdc6e9275dcebff3b7324b864c8f1c12d","observation_id":"93608062-31d4-4a35-8fbb-6efdfc1c72c9","resolution":{"observed_at":"2026-08-07T12:44:06.379726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09110","last_updated":"2023-10-01T21:44:23Z","snapshot_observed_at":"2026-08-10T23:10:13.900680Z","submitted_at":"2022-11-16T18:51:34Z","title":"Holistic Evaluation of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09110","snapshot_observed_at":"2026-08-07T12:44:06.487420Z","title":"Holistic evaluation of language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.487420Z"},"links":{"cited_paper":"/paper/2211.09110","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:cdb60a6f4e16bb40e00d879564b59b9e01a7864135ecec930f35b99505b3f1e5","observation_id":"ed57de1c-10d0-4c87-bbb7-59015f1042b5","resolution":{"observed_at":"2026-08-07T12:44:06.487420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06550","last_updated":"2023-12-11T17:39:00Z","snapshot_observed_at":"2026-08-10T20:06:30.348234Z","submitted_at":"2023-12-11T17:39:00Z","title":"LLM360: Towards Fully Transparent Open-Source LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06550","snapshot_observed_at":"2026-08-07T12:44:06.582871Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.582871Z"},"links":{"cited_paper":"/paper/2312.06550","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:29ffedd04c648ee5296a1533ba4236f3a8c2a63237ae72e494710e1a6cb79d92","observation_id":"5c37eec7-22df-448d-a84f-8018da31cfc8","resolution":{"observed_at":"2026-08-07T12:44:06.582871Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15126","last_updated":"2024-06-14T07:47:09Z","snapshot_observed_at":"2026-08-10T18:53:57.762381Z","submitted_at":"2024-06-14T07:47:09Z","title":"On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15126","snapshot_observed_at":"2026-08-07T12:44:06.650241Z","title":"On llms-driven synthetic data generation, curation, and evaluation: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.650241Z"},"links":{"cited_paper":"/paper/2406.15126","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:80e77756311663a99fb48771932610751adb0e25ee20810d058c1bdf950d5aeb","observation_id":"b8060b6a-96bb-4117-b0b6-c8d9a0695d7d","resolution":{"observed_at":"2026-08-07T12:44:06.650241Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08239","last_updated":"2025-08-20T16:27:42Z","snapshot_observed_at":"2026-08-07T20:57:51.388258Z","submitted_at":"2024-09-12T17:39:08Z","title":"Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08239","snapshot_observed_at":"2026-08-07T12:44:06.723738Z","title":"Source2synth: Synthetic data generation and curation grounded in real data sources","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.723738Z"},"links":{"cited_paper":"/paper/2409.08239","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:bab9b0866e09dc4a3f461feeda9a6783518b0bce458178870deb4e693369ac8c","observation_id":"190610bc-aa42-4dab-a69d-63965aa93ca5","resolution":{"observed_at":"2026-08-07T12:44:06.723738Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03537","last_updated":"2024-12-04T18:32:42Z","snapshot_observed_at":"2026-08-11T22:15:22.514753Z","submitted_at":"2024-12-04T18:32:42Z","title":"Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03537","snapshot_observed_at":"2026-08-07T12:44:06.805147Z","title":"Evaluating gender bias transfer between pre-trained and prompt-adapted language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.805147Z"},"links":{"cited_paper":"/paper/2412.03537","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:a07b9cb91196a5e4057ea5e57f4bab2d500ad9d15d2f688a9686478dc802e5e1","observation_id":"37ba8572-2415-45f1-b527-dda068d2b790","resolution":{"observed_at":"2026-08-07T12:44:06.805147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.17750","last_updated":"2023-10-26T19:45:06Z","snapshot_observed_at":"2026-08-10T20:14:16.170396Z","submitted_at":"2023-10-26T19:45:06Z","title":"A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.17750","snapshot_observed_at":"2026-08-07T12:44:06.883827Z","title":"A framework for automated measurement of responsible ai harms in generative ai applications","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.883827Z"},"links":{"cited_paper":"/paper/2310.17750","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:ea5c1e2caa37ff8d20226293f448d725fb41d0b81080beeafdfb1d01e365e869","observation_id":"a43f5682-4979-40b6-b714-e9d7d0cd7509","resolution":{"observed_at":"2026-08-07T12:44:06.883827Z","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":"2026-08-07T12:44:13.983420Z","title":"and Gales, M","venue":null,"work_id":"4d7d9977-3bb0-4e6d-9bab-35ceea3d00ab","year":2018},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:06.972327Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:bbc5b6216304f1fb007aaf2ba192607d440f543db370cc50d6dda79b7b7c2b13","observation_id":"986efc7f-cdd7-48e2-b41a-8ef9f8391113","resolution":{"observed_at":"2026-08-07T12:44:14.072206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:13.763273Z","title":"and Gales, M","venue":null,"work_id":"4f390a13-34d5-4a18-ac20-66de2d38f382","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.051795Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:e26acdd7c306521643b6281f8db01f746fe6c2b85f4458f953d4ff505f3613c9","observation_id":"bc03394f-a456-45c1-86b3-ac74de6fbd20","resolution":{"observed_at":"2026-08-07T12:44:13.866293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:13.532814Z","title":"Evaluating the fairness of deep learning uncertainty estimates in medical image analysis","venue":null,"work_id":"d38b95bc-5fea-4bc4-b167-e8eb21fec85c","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.150223Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:ca578bdc507aad04140fec332b817dd2c7ff26f6149877d1c68b2f0c3c8004f0","observation_id":"7aa93660-61a2-4b76-bf59-ea5c3b3b8699","resolution":{"observed_at":"2026-08-07T12:44:13.603256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03182","last_updated":"2024-11-19T05:57:28Z","snapshot_observed_at":"2026-08-10T19:43:21.941975Z","submitted_at":"2024-10-04T06:45:48Z","title":"Generating bilingual example sentences with large language models as lexicography assistants","version":2},"cited_work":{"arxiv_id":"2410.03182","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.03182","snapshot_observed_at":"2026-08-07T12:44:09.568948Z","title":"Generating bilingual example sentences with large language models as lexicography assistants","venue":"cs.CL","work_id":"cdcdbc0e-cd15-449d-999f-fa3766437292","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.247063Z"},"links":{"cited_paper":"/paper/2410.03182","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:879d367af5db28fcfafe6e8b42b69bf9afa4c7fbaeab538a8075e4b445c0198b","observation_id":"ff0b5150-4447-45d4-810e-feb529786347","resolution":{"observed_at":"2026-08-07T12:44:09.604411Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:13.323867Z","title":"Hello gpt-4o","venue":null,"work_id":"3595d2ab-bba1-4a4f-bb1f-6303bb4bb726","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.347167Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:457caa73992c41d612cfa6518e774a65e5278a4a602c341cdddc8f25664abcee","observation_id":"0b83949e-8187-4a92-b7ee-916b7b228c06","resolution":{"observed_at":"2026-08-07T12:44:13.448978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:13.140510Z","title":"and Belinkov, Y","venue":null,"work_id":"b2643ec0-c31a-4bb1-9fa9-37d9f9c507bf","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.400920Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:024e5ef4bbeeaedb64003980548b30a6b97c489a7d86d2fee616f0239f741d3e","observation_id":"a7ccdea4-cad3-47df-94e5-c2d781ab555f","resolution":{"observed_at":"2026-08-07T12:44:13.246142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:13.029966Z","title":"and Dadu, T","venue":null,"work_id":"cb160c40-6a06-4fd7-8507-bd7afff1b70b","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.464480Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:95c50c1924f7707d2423da71039bbcaf9aa8b71c762afc1471448247ee2e2069","observation_id":"080825fe-b0c6-4077-b4fd-eae37930262f","resolution":{"observed_at":"2026-08-07T12:44:13.070066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:12.835215Z","title":"M., and Bowman, S","venue":null,"work_id":"636713e0-1bfc-4a22-8468-5dbb79df8c72","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.518970Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:13ede2aceed410613a43326ff96c1ee8d98810586351dba4add6766a095bc3c2","observation_id":"a1cc53cf-7381-44da-9b27-7aabd0d6d0f2","resolution":{"observed_at":"2026-08-07T12:44:12.923793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:12.588291Z","title":"Fairness dynamics during training","venue":null,"work_id":"698f9331-7001-47a5-aca4-acceb1478b82","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.595140Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:c1d8e6da374fd3300c64dce720df289a82cab15cf556f942cefe836604051657","observation_id":"7abc9686-1d84-46db-8ca5-a19c3f50b5ce","resolution":{"observed_at":"2026-08-07T12:44:12.702347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:12.468178Z","title":null,"venue":null,"work_id":"7994e165-444d-4869-89da-da2a061f9762","year":1987},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.677097Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:3d5f69c5b4fadc910667adcebbc0de0bd9b8191e5af660d3bc515e5f5da02091","observation_id":"0eceaf29-1f90-421e-bc81-9d8525091801","resolution":{"observed_at":"2026-08-07T12:44:12.519639Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:12.311676Z","title":"Gender bias in coreference resolution","venue":null,"work_id":"a5cfec2f-bf96-4500-a233-358326e0e7c6","year":2018},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.748722Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:1d88995c5c296c7135c2816dabff17324f528393a8c2585a61314c255c08595f","observation_id":"4e2d420a-72ca-49aa-8d5c-57daf073d835","resolution":{"observed_at":"2026-08-07T12:44:12.383043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:12.137869Z","title":"On a spurious interaction between uncertainty scores and answer evaluation metrics in generative qa tasks","venue":null,"work_id":"47354341-68b4-4073-8e2a-e5dac6e074ad","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.829552Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:e538c5bd085f564eaefcc3176f825ba3f414c48bb7e2b932524dfaf12c4f4e15","observation_id":"958ebc35-214a-45d1-a006-9d662d28e1be","resolution":{"observed_at":"2026-08-07T12:44:12.194166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.13677","last_updated":"2025-06-04T15:25:43Z","snapshot_observed_at":"2026-08-07T16:01:08.210801Z","submitted_at":"2025-04-18T13:13:42Z","title":"Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.13677","snapshot_observed_at":"2026-08-07T12:44:07.914440Z","title":"Revisiting uncertainty quantification evaluation in language models: Spurious interactions with response length bias results","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.914440Z"},"links":{"cited_paper":"/paper/2504.13677","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:9475718a6ce0ce9b3242f9da23163df8932f3d1d91784e96ea7161e5600d71f8","observation_id":"7712e29a-8602-41ff-b653-2b011e338e13","resolution":{"observed_at":"2026-08-07T12:44:07.914440Z","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":"2026-08-07T12:44:11.981064Z","title":"Bridging the gulf of envisioning: Cognitive challenges in prompt based interactions with llms","venue":null,"work_id":"1646f1a1-ddf3-4865-8e32-a9c7a9dc0c02","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:07.989977Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:92b3e42a07457a4cdaf9c25c1ebcb83c0f7f0d1a1f703a65fc493d43fe06b52c","observation_id":"84df99f1-55ea-4914-b97a-8800a882a66d","resolution":{"observed_at":"2026-08-07T12:44:12.045890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:11.827567Z","title":"Fairness through aleatoric uncertainty","venue":null,"work_id":"806f20d9-fc3c-46eb-8ca9-51f783d3c0f3","year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.091691Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:2527c085e1983ce5eb9ecd3a68fe55c02f846979d83318dab80da6217a4b59bb","observation_id":"ecb50084-0ea1-4800-a013-11d06d04ede0","resolution":{"observed_at":"2026-08-07T12:44:11.905507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14825","last_updated":"2023-06-08T16:38:51Z","snapshot_observed_at":"2026-07-06T15:32:18.583350Z","submitted_at":"2023-05-24T07:33:34Z","title":"Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14825","snapshot_observed_at":"2026-08-07T12:44:08.172414Z","title":"Large language models are in-context semantic reasoners rather than symbolic reasoners","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.172414Z"},"links":{"cited_paper":"/paper/2305.14825","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:9784c542039402cc68d80a12d732b7f6ad9a59267e7fdca03566206d1fc29aa1","observation_id":"065c93eb-75d1-4fd3-b75f-094b352369ae","resolution":{"observed_at":"2026-08-07T12:44:08.172414Z","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":"2026-08-07T12:44:11.656626Z","title":"Neutral rewriter: A rule-based and neural approach to automatic rewriting into gender-neutral alternatives","venue":null,"work_id":"86920024-ff93-4c1e-835a-7f6cf539853a","year":2021},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.274245Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:aa4bc2f002382ab5fa1b25967675c26955231254915696777c683da19a084d22","observation_id":"d9325c48-91b4-46cf-9e20-23c2f8fd48d7","resolution":{"observed_at":"2026-08-07T12:44:11.733827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:11.536648Z","title":"Benchmarking uncertainty quantification methods for large language models with lm-polygraph","venue":null,"work_id":"b28a8617-91ce-4224-8e95-67fcfa4bd1bf","year":2025},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.373913Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:09ce13e50627ecfcad2f054562664e61bb4c4642136cea42b84dd4b68e1d7c85","observation_id":"780a6c53-3f1a-4dae-a695-7afa34d87621","resolution":{"observed_at":"2026-08-07T12:44:11.580721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:11.439228Z","title":"Algorithmic learning in a random world","venue":null,"work_id":"694886c2-57c4-4e52-b86f-4c93a363d055","year":2005},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.446481Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:42893eab593765b81b3a5247ae5853ec2976ccd84a4a1e15288612383f7c15d9","observation_id":"d9244cb2-61cf-4c26-bece-8548ea4c3119","resolution":{"observed_at":"2026-08-07T12:44:11.458730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02408","last_updated":"2025-02-22T02:44:54Z","snapshot_observed_at":"2026-08-10T17:45:01.146019Z","submitted_at":"2024-07-02T16:31:37Z","title":"CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02408","snapshot_observed_at":"2026-08-07T12:44:08.529925Z","title":"Ceb: Compositional evaluation benchmark for fairness in large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.529925Z"},"links":{"cited_paper":"/paper/2407.02408","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:2422aa36283c130628052a7fecc6ed2a2ab19a66c9cc51de73972b7a75ec58ad","observation_id":"f90a1aa3-3dfb-4b9a-8d82-db6904012563","resolution":{"observed_at":"2026-08-07T12:44:08.529925Z","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":"2026-08-07T12:44:11.293194Z","title":"Mind the GAP : A balanced corpus of gendered ambiguous pronouns","venue":null,"work_id":"16cccfcc-a869-47e9-a7a1-8745d8fec14b","year":2018},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.642630Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:a83869e90a304ec6a75a86ec37d5167f1710f59d79d0eb203f6313a452f49311","observation_id":"c3ac7cd2-549b-4096-b7e3-431e89c19d08","resolution":{"observed_at":"2026-08-07T12:44:11.374632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-07T12:44:08.738284Z","title":"Qwen2 technical report, 2024 a","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.738284Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:94e5bf5b1a47c47a477916c2b41b6236b1f3d19e2dec693c480236d9d63d6cba","observation_id":"a658f896-e97f-4553-9944-6106e59085d4","resolution":{"observed_at":"2026-08-07T12:44:08.738284Z","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":"2026-08-07T12:44:11.136789Z","title":"Assessing adversarial robustness of large language models: An empirical study","venue":null,"work_id":"5622110d-cf9f-4277-a208-ff96702b99ac","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.814982Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:7642257ded0c93fc47edeb4cae3ba3ad141d8c3730b6c1c053705a4b81bebaf7","observation_id":"7e3c58a4-7fcf-4f83-828f-e04a3ec4b2f7","resolution":{"observed_at":"2026-08-07T12:44:11.240768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.12794","last_updated":"2024-10-31T16:58:51Z","snapshot_observed_at":"2026-08-04T22:23:07.327411Z","submitted_at":"2024-01-23T14:29:17Z","title":"Benchmarking LLMs via Uncertainty Quantification","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.12794","snapshot_observed_at":"2026-08-07T12:44:08.930215Z","title":"F., Yilmaz, E., Shi, S., and Tu, Z","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:08.930215Z"},"links":{"cited_paper":"/paper/2401.12794","citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:424d82621cbcddc76b8ab53adfcd55795b71af22eee9157a4a2508ae01cc1084","observation_id":"d80b6f44-9edc-4ea3-83ec-098c3230df77","resolution":{"observed_at":"2026-08-07T12:44:08.930215Z","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":"2026-08-07T12:44:11.020047Z","title":"Learning uncertainty for unknown domains with zero-target-assumption","venue":null,"work_id":"e9b7bf4f-3216-45ed-8b47-19608c9d5179","year":2022},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:09.049964Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:365bbecd70b9a2a0d3b78263606ab1f6763646284eae1db3581833a7ee0a984a","observation_id":"11d63f38-699a-42a7-9fe3-16447cb6de7c","resolution":{"observed_at":"2026-08-07T12:44:11.069281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:10.876063Z","title":"Gender bias in coreference resolution: Evaluation and debiasing methods","venue":null,"work_id":"8eca3f45-29c7-4486-90a0-a86f838d3d8c","year":2018},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:09.131438Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:e78b8d00bf2bb9ec9459996308b64115d32da5e52c8ba1a830935f0d5b7c9df4","observation_id":"415ad7f8-1cf5-475d-a7ca-2a794fbac504","resolution":{"observed_at":"2026-08-07T12:44:10.943822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:10.734341Z","title":"D., Ren, X., and Sap, M","venue":null,"work_id":"e56788dc-31d9-4515-a90f-f48d79455159","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:09.144729Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:07985da10051f742807e1d583455b346f5e1f3e5e3c0678be6358c1f8bda19dc","observation_id":"c6407c36-553b-4e56-8f28-f55ec6302ac6","resolution":{"observed_at":"2026-08-07T12:44:10.797775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:10.621510Z","title":"P ro SA : Assessing and understanding the prompt sensitivity of LLM s","venue":null,"work_id":"d5513963-1b7d-49f3-b409-21f2dc92f305","year":2024},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:09.153192Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:b7dd8d22dd21a97432f9e8367e416c784e22f4b4fb4ad71382d59719b2e0e232","observation_id":"d2d9b7fe-f93c-4b89-9a1e-e1b28aea42d0","resolution":{"observed_at":"2026-08-07T12:44:10.671673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-07T12:44:09.237881Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-07T12:44:09.237881Z"},"links":{"citing_paper":"/paper/2505.23996"},"observation_digest":"sha256:397979b3b5154d7ea2527648e8708aade623b7f62e6fd8a93b950bcee39e09ba","observation_id":"12102b32-ec44-47e2-a884-42cbca038b9b","resolution":{"observed_at":"2026-08-07T12:44:09.237881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.23996","last_updated":"2025-05-29T20:45:18Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T21:00:36.726464Z","submitted_at":"2025-05-29T20:45:18Z","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs"},"reference_resolution":{"displayed":83,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":34,"verified_exact":4,"verified_fuzzy":45},"total_outbound_references":83},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 1 inbound Pith citation observation for arXiv:2505.23996."}