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Paper Citation Record · LEDGER

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

As of 23 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 2026-08-23T06:30:58.430688+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=sha256:9571bc055f4476fe7d8de645c2678e5e05eff4f03262864e3df938352e43c7af

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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unresolved
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=sha256:6b1f4b5f174b3572363b264e4b68f11be0b28513cac7a8ab3474165bf01cfdcf

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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unresolved
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=sha256:14e9a46fe2d9af6e94e800046795d2c46aa2949e53163f6541a0c519f5e3fecc

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:ba1977baa8c78cef81c32277178146cb84abadf7178b2a5be93f145e40752c98

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.429252Z digest=sha256:b4755f8d16b892b04b028947f6d6320fa0b2e7bece86f16a0c58b4934efaacb0

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.498718Z digest=sha256:62eb2e29dc887dfb9f71cc6de95f7f9dba526af4ea0b66caa6631c89f5376d86

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:e7ba92bf22bdf3e326e209a70de96b8491b2f308d6846359e21cc835dcd15baa

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.679608Z digest=sha256:be78443ca234a1f6c6d05cbb2828e01e5f08b78815c439a7aafe01381c0e3e20

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.765386Z digest=sha256:d4c1712738f0af8e3104b6cf9ede5165cb17dc0abf3f31b6c058b130e61d327b

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:03.882239Z digest=sha256:89356da48fb6375dfcc3c4af039a0a879a6cf38c46e4e3a963a0316346ba8495

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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unresolved
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=sha256:0307b036cb19f6abbc3330055343ed8477e1131e435d7703089f84fabc804c70

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.025627Z digest=sha256:595427971a1b7e025dde80aae058352cc632bc5d52fa8aab1134096a9bcfc433

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.070551Z digest=sha256:78e4de33eea5ab16a193c10573bcee5f0e241a02fa28b1b8fb1dadd71528cdc7

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=sha256:15cf854b1e49ff61c963dec481952eb1dfefa2fe20c6ba2ce8d0c2ee2c1b21ac

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.181777Z digest=sha256:5f80f194a8ec88426ea83bcd3480d39e12607f4f27b70c7400898440fa08f01c

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.225529Z digest=sha256:fe243d9dc76678a4cab676191f9f6ecb4a808a10efd4f0871679973a5aa2abc4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.262182Z digest=sha256:4f7b9cfc009d653b3c8ed2a2d94ada2f4669c32e7633f8bdbb7a8124ad97a4c4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.335390Z digest=sha256:829da511bc1ba86dffaee2ca6fb1c02d67c489d3f5d3c0df726dfe22395260c3

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

Resolution
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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.442745Z digest=sha256:1e98e42bdb67399338e0fc390df116201c4e67975a3b81fe95b97ebc7eed4fee

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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.626150Z digest=sha256:702f91d1d12fe07ae416749a9e5e1c6780db11cfa767e3ac641a8083e13c9d0a

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

Resolution
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 2026-08-23T06:30:58.430688+00:00.

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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.742444Z digest=sha256:087cd4e719b9c2726147a42cbaed3bb9927958c92eaab53b159826ee12fb4e2f

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=sha256:3cb278ed677b6e6d53a2ccf83b11a91424e9d947cad6592f88dea74113836146

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

Resolution
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=sha256:1572b7f8e6833def9931d8e445077168dddfb28df2caa434b5291a978ae8daf5

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 2026-08-23T06:30:58.430688+00:00.

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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:04.906843Z digest=sha256:84f4da9a1b2ef482bc1e49ecbdcc7ef29e41f86430f65ea802ff1d3fb4c8745b

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=sha256:45a63e569582f01426a7c7687dd0b936619530dd9f3b29aeb8eb74c87998d934

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=sha256:3ed15147f539b19cac4e80981b014cd09c4780f1665d8b954df468045e9d4462

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

Resolution
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=sha256:43be8983d2f8271db71d92b3666f53493f6f64f1f8bec9e69c39a514b189f776

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

Resolution
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:a8a867c1d4003cfe980ebb0ecfc0462c1bf5a4e912d635c1d481089cda87476b

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.227274Z digest=sha256:628e00568d042646efa22c8cc887b8dd01babd24ccbd3510592e7f80d0efa0cb

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=sha256:044b3826943ac598661d7a2e713fcf859040a127da823eb4f37d731fb53a1078

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:bb4c9a82c567cc0368314fa4700cac4c6f9442a9cfe482060e76518ea0ce9b64

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.547422Z digest=sha256:681031e78ba84f40cc80a2d4ff2ec05c1d3ae5bdc6e2e1539e28d52d56d9e2c7

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=sha256:6ca9574bd71651fdc74345cb3880a3527480ec3103c1771d8b4a0c07800d1cb4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.735181Z digest=sha256:a00228128eea29aa3548a9508a22942e9ba5d4eae154ee3bc271ff890007d9a0

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.784646Z digest=sha256:90296249f65b79ada1290860e8c483b1dd23d9210a7f5d5278ddf219d957594b

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.828207Z digest=sha256:05061d684d0c40186a82e367713a02c37636d42e1fb0566d0688f84639c8d083

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.902880Z digest=sha256:a8927d088c1afbdb2576b5e6436c1c3aa422452398cf8c77cf65c00aa1f9d5e4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:05.969084Z digest=sha256:9dc99071d3a83766c31f62ae7f49fceb4eca7af3789e90c4ea30cf0afcd1a4fd

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.027478Z digest=sha256:3f05692bcc61da0f0e618129b1e0bfc8a4ad7f98b405d4e121022d97997a8fca

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.092077Z digest=sha256:b3b0bdf3ae6a0a629b95aa1b5aaacab72f252e3264fd9c9aa23e9bf01427efe8

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.156859Z digest=sha256:301b99dcf9c8d309f31e1de513b96bc4e1a9e7e9021250743f275484fca543a4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.214632Z digest=sha256:f752dca3e1a5460cedf86ebf865fbd48c1b9d50fe65c68ffefc841856dcaddbf

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.302999Z digest=sha256:45f5700002e2bd6f989789fe724cbb59bc7c01cddcc5630e385c701bca0a843c

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=sha256:1be8f57880ca861f7a64a3426b7070ddaf50c35806b9a2c56e3bd208ab920f53

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:ac627bfc968131f62898e39e3a139f48ad7356c735491c639bdfc08088cba691

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=sha256:441e4eb653faeb7ac2f973adb5fd37992a1d3c87443ee91f1aef958d0f4a52e9

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=sha256:7efa21efc458073f4591dfc8cd3813794266cc698a683570f3798893fc17fc33

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=sha256:50244198f66e4b2cd2dbdb978a2011ca142d585e44223667de4fe6e04a0b917d

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:a145b23c8ef35cb02c97bb903de192da556408e6093ef5b1f63f8914de00fa63

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:b3cdcfba20c73548ef7ae64ad2e9fe3a7a66f6c4f1305b73d7f92a30b7c0bd31

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:06.972327Z digest=sha256:f7b09ce659a89fed66f169e0e09f1efc30526066aa5a368b1a5cb14736985413

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.051795Z digest=sha256:ff7b8dc3a221ff7440af16abbb675783673fb7e07ef361c61bc39a67fdb89b08

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.150223Z digest=sha256:781ec04b85c428ff628eb67dcd3924853b062533ccd47cc0eada5697cfb552dc

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.247063Z digest=sha256:ecc43561b1481e995682e85610c499bca06c5175394f16189dbd1d1ace6ff4f9

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.347167Z digest=sha256:f4c88fb3c8376b9188303e2fb0044fd5d5494b458e96c5df7a29410f26489339

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.400920Z digest=sha256:7b1284a5150e372a588e99c0447627b54d3c1f6e130d969286b3112f16acc8ca

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.464480Z digest=sha256:1ee4a89e468ef62daf05eeaed593eead893fa808c2db6162b3256fa2ec96ad72

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.518970Z digest=sha256:9e9ff4b01c76c7008ca88d20edfab98899f0d73cb7a91aca2a5c69867837a76b

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.595140Z digest=sha256:77e02b2ab5a38e6f047c54cc80548703de2c06c4c71a7134f214d1f49a8b26da

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.677097Z digest=sha256:0d21307175b380028c8ef517f024e4eb97a40cda62fc54a1d2502cb93e876f83

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.748722Z digest=sha256:26b7f2c9698955fc2b88f3fcfce2abf094becf784e7d9223124c91219a58c994

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.829552Z digest=sha256:e89f6b51d74068c75327735582ce3aded48f91c570fd8b31b91fea7f5a08ef87

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:d7e855ef8975dd84567c79652104cb074ab152e56cba110a58d7e0242028d6ee

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:07.989977Z digest=sha256:89814c177d52a2feece562c9b56dddbe77dc971067269d7cdd79916153eaf4cf

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.091691Z digest=sha256:b3d1e3648e98c9b78226d7db55b18c3a8d20a64d0185b408c40bc7d306cdfe94

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:cf40046911943cbebf7a5be23552d7c5419669b47fc1ae63e4c283b3d435ecf4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.274245Z digest=sha256:4fdee016831b47dd6ae35f3d4f5b2c7b8b39221751f1394957312705d276dde1

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.373913Z digest=sha256:2a63d6d9b83da40aa414f389cff6502da001ef0671c7c4e435d7f5acfaff99dd

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.446481Z digest=sha256:504bf1a1f2ed58d59ed168de938985bf03d1ba523a1fc78c7d5412037e7d68f8

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:d881a7ebcfc7dc30652c3190170bb4a869bbcbb57e0c6ad5f3fee196a380f69a

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.642630Z digest=sha256:e81d6c7413a72ffb0b00b1085475f65d488643072f6fa3e783950d5d015a0ca6

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=sha256:87b7654f094a71674d5aa943c60ba3a3eedf750bc633649b6f15f190cb7e28e3

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:08.814982Z digest=sha256:813308bfd8865ad5b6bf25306bc6999a756a73db1ba9987d62eb961c5c2a95de

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:af21bc3c67c7cc9d1ee14aa0e032f39e5d99ffb62a9d9f6620613a46b22b172b

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.049964Z digest=sha256:d4dac7e39359a42fb24ab4c118b16b4ba0bfc2b6f3d7d501c4dc4a519373c8fb

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.131438Z digest=sha256:b6ad782b4615f88e26093b38290156ceac21cb65fdc038af82dcde38190c0638

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.144729Z digest=sha256:e88375fca78b48eda132e4168e36329cb7c79d34cbfe7cb7edf8e72c1e618c75

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T12:44:09.153192Z digest=sha256:9cb69865a564df9e29c2d7e82d90c7cccfa3641258b7a54b21ebe1951c8ae403

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:fbd6c20f759dad0a468c0e7e402e2edeb44bcdf485b3f8053155bdd78224f1ce

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 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-09T23:44:08.610255Z digest=sha256:e0de0da5a1dd97c22117e882ab14bca177de551c740c18e4ac34f97624bfc337