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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.429252Z digest=sha256:d022e04cc3ed0982b13f1d8c6660a07d9b3aa9a008548b93561b39ad6f384f0a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.498718Z digest=sha256:9dc8c21e1dda87dc2ca64a9503f8b1d3eae91b4012e72df9faa5371a6dbd22f6

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

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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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.679608Z digest=sha256:908101b146a074bba4fb4b3940a6b8178e934abe0ddc05c0e41b3aa56028771b

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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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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.765386Z digest=sha256:2f657a3b8ea5986f8330ae28db14a1784476228abb9347f2fc8d80dadd6e7c04

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.882239Z digest=sha256:f1030111f2006a59e15e4ef66624d7b8bda39377c0c0d23dc7c6b17c33df09cd

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

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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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.025627Z digest=sha256:6f545280436eee80f5780a7d0f17d0751c9aa7f4058a6c626cd8c87839bbdf50

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.070551Z digest=sha256:ee2e934a25d9cef9dbd164003bc9ce9dcbdb6998e94d9afff3675622b44c9df0

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.181777Z digest=sha256:31379445f945fdf97b3c8741c1102703eab94bf85ed11879c1dca62ddc6587c3

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.225529Z digest=sha256:7b01aab9d59b95e398b2d60d1b2160dd74eef3bfca0e10315e35750a66c45d76

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.262182Z digest=sha256:cceacb8ddfb926346ef5a4e8be9c21a2b50ec633343e15f1ad2489696d35b0dd

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.335390Z digest=sha256:5c9c20ce197d3ea05ba407a66dc0da8432aa65bac9a388f2cefb45c0e5f0a1f5

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 2026-08-07T06:34:17.273281+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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.531740Z digest=sha256:c96f8e3fd74cfec0efb446728662727327e9f2992e7ab196da9542ffc48a04ff

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 2026-08-07T06:34:17.273281+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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.700794Z digest=sha256:d0a2c2bbb4db1788fe8e3b82437e8c2d09e0947465ca68c41288cf1aefe2a110

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.742444Z digest=sha256:134ea4475333971eec936e41daba7891fcc73ce4f2065b29fba81aa241652a3f

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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unresolved
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.875490Z digest=sha256:3d074e1c1d096e049dd6437b046ee778a6a1a4831dc29aa918dfd2b55b23f964

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.906843Z digest=sha256:76e3fe8a7942f05640ab1eace52ea39d62867d63ddd66c1f212b42652deea9a4

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.227274Z digest=sha256:c01e89760027fbe8421218c269c44931da7000a6cf0a48ee408b53b237fd4a03

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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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

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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=sha256:8affd731352eae529ce5beaebf4913485a318d14ca0bee7fb1320a0c2a1e9327

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.547422Z digest=sha256:0cd7d69081d39081875021d6b8a8c78d4b07e0d2a0af906d3bb8c29265c3d998

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.735181Z digest=sha256:0dcf8bc8ced1a5f048c4517ddf1e1d928787ac5d5d338461ea76907f1075376f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.784646Z digest=sha256:8add6675182bb24edd2139bc078bab044bf54310f3c94866e0e38e6f07994594

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.828207Z digest=sha256:3ec1eaf27629dca1161f0b8845cee105b0a41d1fa3c5c7732e248c87c967c3a3

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.902880Z digest=sha256:1d838a424ae209af9c42df4004378f0bfddc125c68be20171e93bab27db630fd

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.969084Z digest=sha256:0d677d54c96a0a40ce1d51efca97a89cec4baceb5a6cf1708922651cf5746f1a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.027478Z digest=sha256:19bcb4f12d30a0e534fc1b042340d45e2fd78c6f2db62323c2a123ecc268b346

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.092077Z digest=sha256:20bfe6afc0799602e0bafad96a62450aea153e975a310b403d113f3022ac25ae

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.156859Z digest=sha256:b477bd4975745d70072b2f87917c69b982bfde488aeeeabc98921d2464dbdc98

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.214632Z digest=sha256:9e2b8ad4396f7ace75e229f75e9c2c69a897c4e73d1b6772435ff8bc9137892a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.302999Z digest=sha256:c12858d1503c53647c5d0ebbf70e313dc38867bb27f4d3c69d18046e839f0757

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:f04b5de2da3cce6c9d3d494b9ea214c5d0d94258a6d0606f6b68b4a3896be975

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.972327Z digest=sha256:97a60847c79f91dc1581a1ec272236a87ea54428150fe83e9b975a503085c3e1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.051795Z digest=sha256:b5c98501f91045cbb361c8e7447fc643275104cd862e2a4b0d250c57a62ad796

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.150223Z digest=sha256:d54c6c0be14b447a52a2d63270608df30d73d717e523a121d907d3969797e85b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.247063Z digest=sha256:40cc1bf22cbf93f68b8f68d8fa8b26460bfd0f9bb4d460eb9fb94d6cc0fb0139

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.347167Z digest=sha256:3499bfea4e5b52cda4636f4fa8f7d5461b11b22ae39d33f1218930ebd28dc521

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.400920Z digest=sha256:efe88e0288c8b11f4f4200981e0e539046d09a0a13de9758e0097baf8b9f9d8c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.464480Z digest=sha256:a0508fe992c61331f69b258de839d423e51a895df4e9091f8b4c5fd04fc10cd1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.518970Z digest=sha256:c790f0e484897ec89616df317f76860f05ddc965ebacb4a8860cefc72a13fdf8

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.595140Z digest=sha256:ece4cbdd19da0293f82a25f63367c8607115c9750881992d2e4e92b945868617

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.677097Z digest=sha256:907f3004cacfa6b148dd58fbf981c9ec416580568d8286537dec32567afa6c71

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.748722Z digest=sha256:804a0ef4afdeb6cdec6beccc68bc39cf9c7889f3d69f5270eadd2f30ad992af2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.829552Z digest=sha256:0952ba89f6f7c6769af65e524a2d3654ab04b21e18df9d15042e018c17045063

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.989977Z digest=sha256:8691c7fda381469339ffa9bec80f929c6dff4c336fa0665c7d2c90fbf1420217

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.091691Z digest=sha256:2b71c3055ace50d4d7ce7be9ef432f06fc9dc87e45e24cb6326fe364660d135e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.274245Z digest=sha256:5969d7fffe9e723acd194de02eea181e0aa91a77ee252fbfad341ad05e0b06cb

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.373913Z digest=sha256:6349fdaaacc7c72a1102c6f151f1a252feca7c856a2b04a80ef8d5364a399b1c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.446481Z digest=sha256:249fba9f917dc3c27fd0defa19387fabe59a5fc4e70e96f2762fc7c19a4c5c8c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.642630Z digest=sha256:2e3a46bc8352ffca04ee174e345a57438f42e4ba90548cd5337062646a252ec1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.814982Z digest=sha256:4bfeae89beea815948abf4c07df308498b2b3e08b1392253b47c7b9744c6667f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.049964Z digest=sha256:a2271c4e212a36f054a41406120b9a8e6fd917359d326d8faebfada089ceec56

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.131438Z digest=sha256:1ece0c8c1f71fad7ae15a828d2fecfc1a3b76bb2c47000cbca8d57308e411a04

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.144729Z digest=sha256:f76df0898cd343e5764739a093adebcece09f994d5dc8e68d4409a41b5c83138

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.153192Z digest=sha256:8c0be83406bf460bfeedbf48bb65484c884b58eb71b468a82a8eac0770f275bb

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T23:44:08.610255Z digest=sha256:0f910c5d500f5bbd5942b7ff1df25db6403f24ccfcc130506d71522b3614b3e2