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Paper Citation Record · LEDGER

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs

As of 8 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 1 inbound Pith citation observation for arXiv:2505.23996.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.23996 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:44:09.237881Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T23:44:08.610255Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T14:01:06.694928Z

Reference resolution

83 of 83 outbound references displayed

  • verified exact4
  • verified fuzzy45
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 267a49f6-fb9a-4a7f-8ff7-54ad008f1d7b · outbound

This paper cites The Falcon Series of Open Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs The Falcon Series of Open Language Models

Reference 1

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unresolved
no resolver link, observed 2026-08-07T12:44:03.211772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.211772Z digest=sha256:878f5c3aaf614a2ddda62f4416e0d27572c527f82e87ef26fc3a0ec67c894c7e

Observation f17bdf98-f59c-4e2f-9c49-ffbfc88517b7 · outbound

This paper cites The silicon ceiling: Auditing gpt’s race and gender biases in hiring.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs The silicon ceiling: Auditing gpt’s race and gender biases in hiring

Reference 2

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no resolver link, observed 2026-08-07T12:44:03.252351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.252351Z digest=sha256:4831f63559ecd9b0656c2a9218cd342d067d785085f3e4f53239dd972ff32094

Observation eb20950c-fb41-464c-be82-10f0ad4cef28 · outbound

This paper cites V., and Pan, R.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs V., and Pan, R

Reference 3

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no resolver link, observed 2026-08-07T12:44:03.318792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.318792Z digest=sha256:71a8b3e31ec78dc64b9b4e3d693cd04ed55d2c7f40999ae561bd5d4a8dcf9a3b

Observation 9a1bf20c-610a-4515-838d-db79a3dcbf91 · outbound

This paper cites G., Bradley, H., O'Brien, K., Hallahan, E., Khan, M.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs G., Bradley, H., O'Brien, K., Hallahan, E., Khan, M

Reference 4

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unresolved
no resolver link, observed 2026-08-07T12:44:03.379829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.379829Z digest=sha256:0a373a15c143369432f3d5e5c3a95aabc1b9d6c632b7a79252facf88bc055816

Observation 4b8f3a54-d4cd-4adf-8275-7224b04596e9 · outbound

This paper cites Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:18.568953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.429252Z digest=sha256:f6a244bad88f50d99b916038753feb32c2abe4bfc1566613d2c4def9a6de17b8

Observation d5d09ab7-b3de-4c76-8b34-3051c1fea543 · outbound

This paper cites L., Barocas, S., Daum \'e III, H., and Wallach, H.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs L., Barocas, S., Daum \'e III, H., and Wallach, H

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:18.446346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.498718Z digest=sha256:e260b1ef9d1cb5c7bd0053a5f02411e60ce081cb52e99f7af550cd6d7ec18ffe

Observation b195c183-f0c0-4945-8f7a-97224aa9f811 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs On the Opportunities and Risks of Foundation Models

Reference 7

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no resolver link, observed 2026-08-07T12:44:03.586468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.586468Z digest=sha256:a0b3d083180646e1a8f0f85b1b4577073e9dbce561587fb9ee8a3ef03272c3f2

Observation 8d7fc5fa-e812-4860-ae4a-bd43d223fb7b · outbound

This paper cites an unresolved cited work.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:44:18.269199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.679608Z digest=sha256:b906f429ec0ed867bdfb45ba32979a7e46b7565cbf31d99ed73a3dd3e6a3e306

Observation 2d2c9879-b12e-406b-95fe-d252144209f3 · outbound

This paper cites Fairness in large language models: A taxonomic survey.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Fairness in large language models: A taxonomic survey

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:18.121535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.765386Z digest=sha256:30f4273f37ff158a56403d7213cb4102274e862e666c5157797cf493497e76df

Observation 44a6f248-865d-4c73-8c3c-e7ab85da8878 · outbound

This paper cites Rainproof: An umbrella to shield text generators from out-of-distribution data.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Rainproof: An umbrella to shield text generators from out-of-distribution data

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.967413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.882239Z digest=sha256:3bd8fd383a3f51b520460a36ca6abcc66cf8af997f37caf01a7a997878a3a2c8

Observation 197f1aa5-235c-42b4-bf9a-9d1b97938dbc · outbound

This paper cites Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model, 2024.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model, 2024

Reference 11

Resolution
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no resolver link, observed 2026-08-07T12:44:03.975683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:03.975683Z digest=sha256:01bfc0b65cff20be3e7077889bb0112f0b4b2561a884c75021cbc310695e8412

Observation d8a18180-b3b2-4b2b-ac12-3e0bbf980a4d · outbound

This paper cites Bold: Dataset and metrics for measuring biases in open-ended language generation.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Bold: Dataset and metrics for measuring biases in open-ended language generation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.801829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.025627Z digest=sha256:4aedaacb8deb1b166a436ba633d3f072b809dee517097071e322c5c3bd6707d0

Observation a16b8b19-898a-4a4e-9333-0e75f14cea62 · outbound

This paper cites Shifting attention to relevance: Towards the uncertainty estimation of large language models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Shifting attention to relevance: Towards the uncertainty estimation of large language models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.605590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.070551Z digest=sha256:6aa454df6c3f0e6603f2e48ce892ad09fc4dc51b04d4a538087ef5f7750ad634

Observation f07540c8-3e8c-4d6b-b6d7-1b7c067214f3 · outbound

This paper cites The Llama 3 Herd of Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs The Llama 3 Herd of Models

Reference 14

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no resolver link, observed 2026-08-07T12:44:04.134653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:04.134653Z digest=sha256:dbfe37162e94739605a4423c41062dbef7553d9ce91c02397f0501d831835538

Observation 067edf46-7318-4a8c-a34c-f1ebd2cb8b8d · outbound

This paper cites Is your classifier actually biased? measuring fairness under uncertainty with bernstein bounds.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Is your classifier actually biased? measuring fairness under uncertainty with bernstein bounds

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.467523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.181777Z digest=sha256:25eb5518f4870c227b4b7c5f5e046ac62b437cf335cf9456e7eb657ae867e374

Observation b981a3ba-738f-453c-a0e2-c54a7ddaecba · outbound

This paper cites an unresolved cited work.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:44:17.356648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.225529Z digest=sha256:d4fdfc422ec45faf1d1d0a8b8418a64ffb4af815573e424ed27ba9016a276dfc

Observation a794e728-b1be-47e0-8d0c-00adb3cca5db · outbound

This paper cites Lm-polygraph: Uncertainty estimation for language models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Lm-polygraph: Uncertainty estimation for language models

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.221006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.262182Z digest=sha256:1a3decd5651554e4aa43a6b35dee8f4c6ea03f82c2151dce9587e86a668c8c48

Observation 04560253-639a-45fa-ab1e-20c325ac77d3 · outbound

This paper cites L., Waseem, Z., and Tsvetkov, Y.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs L., Waseem, Z., and Tsvetkov, Y

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:17.086920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.335390Z digest=sha256:ba7faff1f5b3ffe52b28d6f7549e4fe45986b43c1ff24d74adbee16c5ce38d91

Observation 5881bbfb-1859-4960-9fc5-00c566e5f496 · outbound

This paper cites Unsupervised quality estimation for neural machine translation.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unsupervised quality estimation for neural machine translation

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-07T12:44:16.952392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a3ca57aa-9d39-4835-8383-bc20007013fd · outbound

This paper cites Open llm leaderboard v2, 2024.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Open llm leaderboard v2, 2024

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f176d5fa-749e-4836-8818-8de98a33160b · outbound

This paper cites and Ghahramani, Z.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Ghahramani, Z

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c804cfaa-d7d0-40c4-938a-ff588d4394ae · outbound

This paper cites O., Rossi, R.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs O., Rossi, R

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:16.417568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.626150Z digest=sha256:386b9f76fcec25e85c23af880d3ecccea837b22da6cac60fa80db59e796c5850

Observation 4ce52675-f329-481b-9b0c-dff3288e3bb1 · outbound

This paper cites an unresolved cited work.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unresolved cited work

Reference 23

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unresolved
raw_fallback, observed 2026-08-07T12:44:16.234860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.700794Z digest=sha256:a5ace34c8a4a0f107b95b94a6d0a4017f48f9eecdf085fc311ddc3b77160f5a0

Observation 6c0d3603-88ef-4ded-8690-bb0e48704e43 · outbound

This paper cites Uncertainty-guided optimization on large language model search trees.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Uncertainty-guided optimization on large language model search trees

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.975896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.742444Z digest=sha256:475538b9ba130dcb5267dee365a2b21a54917cb1c6df8cc6cc2fc16056dbc30d

Observation 845b542b-fc39-4034-8828-2eb489d7e20c · outbound

This paper cites Generative AI for Synthetic Data Generation: Methods, Challenges and the Future.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Generative AI for Synthetic Data Generation: Methods, Challenges and the Future

Reference 25

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no resolver link, observed 2026-08-07T12:44:04.783265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:04.783265Z digest=sha256:578f2a8f67a16bd7a217badbea188860b8e65332a284ca5af874e6d8711fd5d7

Observation aa724e5d-ae6b-46b6-a2ee-261700e5d125 · outbound

This paper cites Bias in Large Language Models: Origin, Evaluation, and Mitigation.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Bias in Large Language Models: Origin, Evaluation, and Mitigation

Reference 26

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unresolved
no resolver link, observed 2026-08-07T12:44:04.836197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:04.836197Z digest=sha256:be3f7e4728ffa198c587a300feab3e35d123cb477fa1fa76061b147df015b3ff

Observation c29870cf-afb8-4327-af8b-e4cde30753af · outbound

This paper cites Equality of opportunity in supervised learning.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Equality of opportunity in supervised learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.828040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.875490Z digest=sha256:e87e9efac6c4184a2e317670eaf148abc409f7682619a7cf1b487f4033b6b5ee

Observation 0cb4e436-10e8-4b55-acc3-40da88540576 · outbound

This paper cites Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.726090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.906843Z digest=sha256:eae890b0ac941322a25cc38c7866b786c2c4e281f4084ce627047669244938bf

Observation fa5f142f-928c-4395-8bff-bf0e042a8f6c · outbound

This paper cites and Gimpel, K.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Gimpel, K

Reference 29

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unresolved
no resolver link, observed 2026-08-07T12:44:04.987792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:04.987792Z digest=sha256:a7eefef77e86b6f946ffde0f7b86080fa4f216dd50507e012451c817c60e6740

Observation f06b45b9-9eb0-4ac7-954f-d7a6bddfdfb3 · outbound

This paper cites Measuring massive multitask language understanding.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Measuring massive multitask language understanding

Reference 30

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unresolved
no resolver link, observed 2026-08-07T12:44:05.064663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.064663Z digest=sha256:3747cba73e3c0855e1f57dbd929c64ec685b65721d2088f20831e71035c78008

Observation 4ba409ec-371a-40b2-88fa-dabdb7518bb9 · outbound

This paper cites Uncertainty in Natural Language Processing: Sources, Quantification, and Applications.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Uncertainty in Natural Language Processing: Sources, Quantification, and Applications

Reference 31

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unresolved
no resolver link, observed 2026-08-07T12:44:05.127538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.127538Z digest=sha256:7191d83aadefb3e841dc04ed313f2d7ad4cf36f0ad2a056a0eff82dd0918d2e2

Observation 17d49396-5d55-4116-ab29-06355a8eb962 · outbound

This paper cites Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models

Reference 32

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unresolved
no resolver link, observed 2026-08-07T12:44:05.183520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.183520Z digest=sha256:3bd1a93d469040a79b9041e9c9a0626a45691229ab64b15f71b6655a6091c438

Observation ab931db8-d725-4743-bc0b-4892c070c473 · outbound

This paper cites L., Bahl, L.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs L., Bahl, L

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.611090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.227274Z digest=sha256:33a5d6529c0bdead700b92534b414763550e8565d48fa992d246ce12a0ff0c8b

Observation 6d655d69-9704-4d5c-b42e-01dd3f4d9694 · outbound

This paper cites Mistral 7B.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Mistral 7B

Reference 34

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unresolved
no resolver link, observed 2026-08-07T12:44:05.361003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.361003Z digest=sha256:c6008d9c0723f1d5d88971c1d2f65c7d79bbed47ebb95938dcd3784d102f4845

Observation 5026a8ab-faef-402c-a3e4-f089bc9f34b3 · outbound

This paper cites Mixtral of Experts.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Mixtral of Experts

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:05.455604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.455604Z digest=sha256:79a9d14fc3129132941298b5034167372438bfe7c27a32d2c21fb430b4f1fae8

Observation be4ed6db-eb0d-4b7c-b080-f07afa408ef9 · outbound

This paper cites and Martin, J.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Martin, J

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.479941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.547422Z digest=sha256:6c3ddcf617770e87bc50f3ec8c5f177c0ee6ca227953bb04e1990182280c9687

Observation cd954028-4c08-49ae-b3df-ff35f7ba38e8 · outbound

This paper cites Language Models (Mostly) Know What They Know.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Language Models (Mostly) Know What They Know

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:05.646636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:05.646636Z digest=sha256:7ae69df8a29f47d5ae24ae1bc83b7ce5eb18e800d85c14bb78e3d0a27c3ae23f

Observation 098ebb9d-4ddc-4ad3-a6ea-73ff101743dc · outbound

This paper cites Uncertainty-aware predictive modeling for fair data-driven decisions.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Uncertainty-aware predictive modeling for fair data-driven decisions

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:44:10.238901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.735181Z digest=sha256:58d016e0d715a85822eb4166d3ce560e64e0a6359c07485bde81744400585ec2

Observation 5f6f6416-8501-4c75-b20c-5f5ead7559e8 · outbound

This paper cites and Gal, Y.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Gal, Y

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.328117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.784646Z digest=sha256:0cfd8b3a9d171f4c9221accd837e563154515b723cac652faa88e93f5a92380a

Observation 9260af03-bf8b-4553-8ec1-c82917700bb1 · outbound

This paper cites Gender bias and stereotypes in large language models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Gender bias and stereotypes in large language models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.221107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.828207Z digest=sha256:578a45e30a85c761b222b7b8a42cab4ecfa53f8c31f0f7a04e2235031c39f690

Observation 798933d2-53db-4aee-ae2e-d36e294ceed5 · outbound

This paper cites Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:15.160020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.902880Z digest=sha256:d270bdd958ebb4507b33d0d8dfa1f89e0944f2eaccd2d8329037a66e2184f9cd

Observation fdff9ccf-e8c2-41ad-91ab-5c9b3c8074de · outbound

This paper cites Uncertainty estimation for debiased models: Does fairness hurt reliability? In Park, J.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Uncertainty estimation for debiased models: Does fairness hurt reliability? In Park, J

Reference 42

Resolution
verified exact
doi, observed 2026-08-07T12:44:15.059129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.969084Z digest=sha256:8d986edbbe2add953c5297ff01e1bb403ea68400305c622f559a56731b213bd3

Observation 333277ac-5c58-449b-97f1-7b9c071e17df · outbound

This paper cites Uncertainty-based Fairness Measures.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Uncertainty-based Fairness Measures

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:44:09.941465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.027478Z digest=sha256:16dd34a31fa7cfdac7258677366d3c8ccf7349400d5f249a2d3b5c1723992a5a

Observation 12e0d74e-0604-4339-b08c-7b1af3110f49 · outbound

This paper cites an unresolved cited work.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:44:14.929638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.092077Z digest=sha256:91252f312cbd370388b71bf2c93e05d23f559d9eb05551370ae2375be2050c3f

Observation f14adab0-3a8c-4588-b257-f1976c23c350 · outbound

This paper cites End-to-end neural coreference resolution.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs End-to-end neural coreference resolution

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:14.769524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.156859Z digest=sha256:1fa4804d36f81581de77e61de5c21c4328e8261c818edb072585d34f835ed6fc

Observation c0bb72c7-a3bc-4e41-b42e-5616ada4bd59 · outbound

This paper cites The winograd schema challenge.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs The winograd schema challenge

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:14.540624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.214632Z digest=sha256:cb1a9741e160de1a1bb4e4a4bf4268ab6073b3693ae9bc23c17fab8708a1f505

Observation 361ca2d0-a944-429a-8d08-d7541daf1106 · outbound

This paper cites Collecting a large-scale gender bias dataset for coreference resolution and machine translation.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Collecting a large-scale gender bias dataset for coreference resolution and machine translation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:14.275121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.302999Z digest=sha256:c7aa6ba60fb1d8583289db493a168a22d2b63763c5bfad9a5c03c9c6155e1653

Observation 93608062-31d4-4a35-8fbb-6efdfc1c72c9 · outbound

This paper cites A Survey on Fairness in Large Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs A Survey on Fairness in Large Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.379726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.379726Z digest=sha256:681005801936723e8f3e0337f7089a7bdc6e9275dcebff3b7324b864c8f1c12d

Observation ed57de1c-10d0-4c87-bbb7-59015f1042b5 · outbound

This paper cites Holistic Evaluation of Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Holistic Evaluation of Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.487420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.487420Z digest=sha256:aed090f992414529fde3d1e659dd943ccc20afe0237d1d4a524dc80a85db0730

Observation 5c37eec7-22df-448d-a84f-8018da31cfc8 · outbound

This paper cites LLM360: Towards Fully Transparent Open-Source LLMs.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs LLM360: Towards Fully Transparent Open-Source LLMs

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.582871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.582871Z digest=sha256:8fce3c39895c2d73bfd4396e48e746545dee9f6aef4ec12955f513e374acd5af

Observation b8060b6a-96bb-4117-b0b6-c8d9a0695d7d · outbound

This paper cites On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.650241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.650241Z digest=sha256:d51558664b3d13b45d7548313952f226644fe412221163eaefef5f3b8a10b145

Observation 190610bc-aa42-4dab-a69d-63965aa93ca5 · outbound

This paper cites Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.723738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.723738Z digest=sha256:bab9b0866e09dc4a3f461feeda9a6783518b0bce458178870deb4e693369ac8c

Observation 37ba8572-2415-45f1-b527-dda068d2b790 · outbound

This paper cites Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.805147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.805147Z digest=sha256:d6b2c30a47bfa595509b44d4227f574c8c9d3efc633b460288efdd05113cddc0

Observation a43f5682-4979-40b6-b714-e9d7d0cd7509 · outbound

This paper cites A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:06.883827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:06.883827Z digest=sha256:ca2017ebe57422429e60bf84dd8e95978c9b1b1f99747076b4c30b1dc5821346

Observation 986efc7f-cdd7-48e2-b41a-8ef9f8391113 · outbound

This paper cites and Gales, M.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Gales, M

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:14.072206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.972327Z digest=sha256:f81f1c10e28c1a657ed4768df213d7a0a123cae029ba72c0c899a4341d099a99

Observation bc03394f-a456-45c1-86b3-ac74de6fbd20 · outbound

This paper cites and Gales, M.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Gales, M

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:13.866293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.051795Z digest=sha256:bbc03f8cad918233d9d619cc0a6e84f2f7f24554a9796716c6345ec350dcc786

Observation 7aa93660-61a2-4b76-bf59-ea5c3b3b8699 · outbound

This paper cites Evaluating the fairness of deep learning uncertainty estimates in medical image analysis.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Evaluating the fairness of deep learning uncertainty estimates in medical image analysis

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:13.603256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.150223Z digest=sha256:945f29f1718e818e729b34f3e02fd7653369f67152079334b462472aef24aae1

Observation ff0b5150-4447-45d4-810e-feb529786347 · outbound

This paper cites Generating bilingual example sentences with large language models as lexicography assistants.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Generating bilingual example sentences with large language models as lexicography assistants

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:44:09.604411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.247063Z digest=sha256:641f84ec0adfb7b1d2273523093bb1a8e2593bb27c0fd14bb4bf9d18a4c05630

Observation 0b83949e-8187-4a92-b7ee-916b7b228c06 · outbound

This paper cites Hello gpt-4o.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Hello gpt-4o

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:13.448978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.347167Z digest=sha256:1d019d573a72d0ffb398aa03540196e465ae2c3a5a5933828246c46e3721f2b4

Observation a7ccdea4-cad3-47df-94e5-c2d781ab555f · outbound

This paper cites and Belinkov, Y.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Belinkov, Y

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:13.246142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.400920Z digest=sha256:63ca91614339f4256a18ca1874bec5fc43adf60cee3adaee63adbac5386bb204

Observation 080825fe-b0c6-4077-b4fd-eae37930262f · outbound

This paper cites and Dadu, T.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs and Dadu, T

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:13.070066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.464480Z digest=sha256:db2ff5a0111474bbc8dc70c38422e265b128b378db31b96fa49584957cbb67b0

Observation a1cc53cf-7381-44da-9b27-7aabd0d6d0f2 · outbound

This paper cites M., and Bowman, S.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs M., and Bowman, S

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:12.923793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.518970Z digest=sha256:340b5425f19e7881361f0b70bc6256f33540aeea73d3b6c6a121917fbd357f97

Observation 7abc9686-1d84-46db-8ca5-a19c3f50b5ce · outbound

This paper cites Fairness dynamics during training.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Fairness dynamics during training

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:12.702347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.595140Z digest=sha256:314bca69b7c21a48204d364ab890f45e6a7cb98206ce06ff83225b05d853fc60

Observation 0eceaf29-1f90-421e-bc81-9d8525091801 · outbound

This paper cites an unresolved cited work.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:44:12.519639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.677097Z digest=sha256:96aff5c42f9b56b0741da34412952ca58f71f24ff07890d3fa616dd8b23f5b14

Observation 4e2d420a-72ca-49aa-8d5c-57daf073d835 · outbound

This paper cites Gender bias in coreference resolution.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Gender bias in coreference resolution

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:12.383043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.748722Z digest=sha256:4fe53f4e4af70ea9277e0b4d15dd0ce3150fe8fca9ef39f3d9889f406013fa12

Observation 958ebc35-214a-45d1-a006-9d662d28e1be · outbound

This paper cites On a spurious interaction between uncertainty scores and answer evaluation metrics in generative qa tasks.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs On a spurious interaction between uncertainty scores and answer evaluation metrics in generative qa tasks

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:12.194166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.829552Z digest=sha256:5cb5fe687b8a92161debd71e83eb5be6f10999e759305a9a8d0c4b8d32cd99e2

Observation 7712e29a-8602-41ff-b653-2b011e338e13 · outbound

This paper cites Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:07.914440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:07.914440Z digest=sha256:9475718a6ce0ce9b3242f9da23163df8932f3d1d91784e96ea7161e5600d71f8

Observation 84df99f1-55ea-4914-b97a-8800a882a66d · outbound

This paper cites Bridging the gulf of envisioning: Cognitive challenges in prompt based interactions with llms.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Bridging the gulf of envisioning: Cognitive challenges in prompt based interactions with llms

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:12.045890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.989977Z digest=sha256:48384267dda3fed066dca8ee28e4a3707393aa211ca347057088463ea1da610c

Observation ecb50084-0ea1-4800-a013-11d06d04ede0 · outbound

This paper cites Fairness through aleatoric uncertainty.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Fairness through aleatoric uncertainty

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.905507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.091691Z digest=sha256:69dc94484c7dc0907039c9de28fa3d6294a3c2bda8e7ff9a9a54cd81d35c0677

Observation 065c93eb-75d1-4fd3-b75f-094b352369ae · outbound

This paper cites Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:08.172414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:08.172414Z digest=sha256:9784c542039402cc68d80a12d732b7f6ad9a59267e7fdca03566206d1fc29aa1

Observation d9325c48-91b4-46cf-9e20-23c2f8fd48d7 · outbound

This paper cites Neutral rewriter: A rule-based and neural approach to automatic rewriting into gender-neutral alternatives.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Neutral rewriter: A rule-based and neural approach to automatic rewriting into gender-neutral alternatives

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.733827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.274245Z digest=sha256:5c6c3c09ec39848d9e32abfe1d797e7a5f17e0432f34c802e3d2a35ea3640c4d

Observation 780a6c53-3f1a-4dae-a695-7afa34d87621 · outbound

This paper cites Benchmarking uncertainty quantification methods for large language models with lm-polygraph.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Benchmarking uncertainty quantification methods for large language models with lm-polygraph

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.580721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.373913Z digest=sha256:7ec5fade6c020853a0569569f28b00bd31893f70d5c84518608a0173aac727e3

Observation d9244cb2-61cf-4c26-bece-8548ea4c3119 · outbound

This paper cites Algorithmic learning in a random world.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Algorithmic learning in a random world

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.458730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.446481Z digest=sha256:9cf538261446a07f302ee8a8753747025d00c62714b08967312903a1c4ae9fa3

Observation f90a1aa3-3dfb-4b9a-8d82-db6904012563 · outbound

This paper cites CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:08.529925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:08.529925Z digest=sha256:37c0802982e7685f7b586eaa429206f3ef501991c818900c9fc1031c574d47f6

Observation c3ac7cd2-549b-4096-b7e3-431e89c19d08 · outbound

This paper cites Mind the GAP : A balanced corpus of gendered ambiguous pronouns.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Mind the GAP : A balanced corpus of gendered ambiguous pronouns

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.374632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.642630Z digest=sha256:6f062d7afa6d36cacb4acfcfb95e50d06f0970c3024d3e14f123dd1dfbfad6f4

Observation a658f896-e97f-4553-9944-6106e59085d4 · outbound

This paper cites Qwen2 Technical Report.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Qwen2 Technical Report

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:08.738284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:08.738284Z digest=sha256:94e5bf5b1a47c47a477916c2b41b6236b1f3d19e2dec693c480236d9d63d6cba

Observation 7e3c58a4-7fcf-4f83-828f-e04a3ec4b2f7 · outbound

This paper cites Assessing adversarial robustness of large language models: An empirical study.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Assessing adversarial robustness of large language models: An empirical study

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.240768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.814982Z digest=sha256:e5c7e9ac22142d0c0e651e34a47f03aac918bb77aa55fc271bb95f692d8a26cb

Observation d80b6f44-9edc-4ea3-83ec-098c3230df77 · outbound

This paper cites Benchmarking LLMs via Uncertainty Quantification.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Benchmarking LLMs via Uncertainty Quantification

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:08.930215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:08.930215Z digest=sha256:424d82621cbcddc76b8ab53adfcd55795b71af22eee9157a4a2508ae01cc1084

Observation 11d63f38-699a-42a7-9fe3-16447cb6de7c · outbound

This paper cites Learning uncertainty for unknown domains with zero-target-assumption.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Learning uncertainty for unknown domains with zero-target-assumption

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:11.069281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.049964Z digest=sha256:f27981ec3c1e46b96c452f44076bd64e2d7acec4214d405edb9921314c500e3a

Observation 415ad7f8-1cf5-475d-a7ca-2a794fbac504 · outbound

This paper cites Gender bias in coreference resolution: Evaluation and debiasing methods.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Gender bias in coreference resolution: Evaluation and debiasing methods

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:10.943822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.131438Z digest=sha256:715ba3e4deb3f08dcd8b8c07b13cf9774430d122bdd0cde57c7ad65ab89f969d

Observation c6407c36-553b-4e56-8f28-f55ec6302ac6 · outbound

This paper cites D., Ren, X., and Sap, M.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs D., Ren, X., and Sap, M

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:10.797775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.144729Z digest=sha256:f02748071e048b5b37d26c629511efe5a5a80d168315591c1a0a93c5c404ed32

Observation d2d9b7fe-f93c-4b89-9a1e-e1b28aea42d0 · outbound

This paper cites P ro SA : Assessing and understanding the prompt sensitivity of LLM s.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs P ro SA : Assessing and understanding the prompt sensitivity of LLM s

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:44:10.671673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.153192Z digest=sha256:1da4e2d3053c4c950b6235fb7c0ac938720f6ad550057f9acd73df0a0b3ebe11

Observation 12102b32-ec44-47e2-a884-42cbca038b9b · outbound

This paper cites write newline.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs write newline

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:09.237881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:09.237881Z digest=sha256:397979b3b5154d7ea2527648e8708aade623b7f62e6fd8a93b950bcee39e09ba

Pith citing papers

Observation d0b62ad9-d922-4ad0-984c-6955fa824d9b · inbound

Intersectional Fairness in Large Language Models cites this paper.

Intersectional Fairness in Large Language Models Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:01:06.699849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T23:44:08.610255Z digest=sha256:ef2c2ca83081a4878786632c9492d1d4bf98696d48083791a675732f6f886e59