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Paper Citation Record · LEDGER

Towards Effective Discrimination Testing for Generative AI

As of 14 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2412.21052.

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

pith.paper-citation-record.v1
2412.21052 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:08:45.205423Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31c91f13-db56-4c29-84dc-70653bbb41e1 · outbound

This paper cites What is your least favourite thing about GROUP people?.

Towards Effective Discrimination Testing for Generative AI What is your least favourite thing about GROUP people?

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c93d6f05-293f-4694-83ec-c08040ca669e · outbound

This paper cites What Will it Take to Fix Benchmarking in Natural Language Understanding?.

Towards Effective Discrimination Testing for Generative AI What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 7

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source=pdf_text observed=2026-08-10T23:08:44.109938Z digest=sha256:315307a2d03d392498846618946a91d9b736fa3fdbc459efb7a01f8ce8335f34

Observation b4d9e0b9-d556-4411-97e0-8b7c9a55261e · outbound

This paper cites Cfpb circular 2022-03: Adverse action notification requirements in connection with credit decisions based on complex algorithms,.

Towards Effective Discrimination Testing for Generative AI Cfpb circular 2022-03: Adverse action notification requirements in connection with credit decisions based on complex algorithms,

Reference 8

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6dd68368-0ee1-4446-8ed1-99765f8fdeee · outbound

This paper cites DALL-EV AL: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models.

Towards Effective Discrimination Testing for Generative AI DALL-EV AL: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.245531Z digest=sha256:b058f23bb81ba9ce3150b9f188ae6c8c6f07322097d4f8493aa16b4a0722740a

Observation 53db85ff-e855-43f3-a989-068d695769e1 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Towards Effective Discrimination Testing for Generative AI Training Verifiers to Solve Math Word Problems

Reference 10

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source=pdf_text observed=2026-08-10T23:08:44.353142Z digest=sha256:4105d4c1137db58bb2649843e547606b203cd4616e1e8cf71b6b9881759c7c15

Observation 26b7423a-7215-4fd5-8be5-013f01ca5e78 · outbound

This paper cites Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification.

Towards Effective Discrimination Testing for Generative AI Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification

Reference 11

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source=pdf_text observed=2026-08-10T23:08:44.408470Z digest=sha256:17aa3554dffa5ab8c310948c0aae015134b2ba20ab1947312423a7360f24de24

Observation 506a2e4e-e9c5-4075-9c07-4ae498c6edd3 · outbound

This paper cites Patton, Elsbeth Turcan, and Kathleen McKeown.

Towards Effective Discrimination Testing for Generative AI Patton, Elsbeth Turcan, and Kathleen McKeown

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.418503Z digest=sha256:c79fdb7b183582dd23420e8b2bd063ff12106c63f45ee8c53650c845041e5c1c

Observation 0f4e0725-a4d3-453b-955f-87ed3bce7ba9 · outbound

This paper cites Directive 2000/43/ec implementing the principle of equal treatment between persons irrespective of racial or ethnic origin,.

Towards Effective Discrimination Testing for Generative AI Directive 2000/43/ec implementing the principle of equal treatment between persons irrespective of racial or ethnic origin,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.424588Z digest=sha256:edbad15dce5990a6b9405fbfb964eb0346796c99289869d6305f80865a22f734

Observation 4678ae47-3298-4fb4-b851-1bb2bcbcb161 · outbound

This paper cites The Llama 3 Herd of Models.

Towards Effective Discrimination Testing for Generative AI The Llama 3 Herd of Models

Reference 16

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source=pdf_text observed=2026-08-10T23:08:44.562466Z digest=sha256:7ee6cd0982b9726000c79a4393c08f6e15c78cb69aa6507133052c92a9c21db7

Observation ba2e434e-2397-4428-b00a-249cd359bb95 · outbound

This paper cites On the impact of machine learning randomness on group fairness.

Towards Effective Discrimination Testing for Generative AI On the impact of machine learning randomness on group fairness

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.683567Z digest=sha256:ed9e4d91527f0cf0b657c85cae4a146f74ff8a8b0b9e83e13b4e28d62b3d7a1d

Observation 5ca07260-3a52-4c7b-818d-04f9dcae9dc0 · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

Towards Effective Discrimination Testing for Generative AI Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 19

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source=pdf_text observed=2026-08-10T23:08:44.690397Z digest=sha256:f4ba040ed5840116507cabd5ea58ebd27c2cff22d6e80f9fb2b725ed7c9cf903

Observation 987067d8-efb7-4e4d-8a0c-0b221843428b · outbound

This paper cites Chatgpt perpetuates gender bias in machine translation and ignores non-gendered pronouns: Findings across bengali and five other low-resource languages.

Towards Effective Discrimination Testing for Generative AI Chatgpt perpetuates gender bias in machine translation and ignores non-gendered pronouns: Findings across bengali and five other low-resource languages

Reference 20

Resolution
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raw_fallback, observed 2026-08-10T23:08:46.502506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.696870Z digest=sha256:0d3868272a7fc13360b31ad9131c352aff5f7baf4c7b5fd416ee52adbd91b9cd

Observation cf6df869-a036-451f-8d9c-895131e8ebf6 · outbound

This paper cites Operationalizing the search for less discriminatory alternatives in fair lending.

Towards Effective Discrimination Testing for Generative AI Operationalizing the search for less discriminatory alternatives in fair lending

Reference 21

Resolution
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raw_fallback, observed 2026-08-10T23:08:46.483653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.706404Z digest=sha256:15a820dde6221d8f1a3e9e4612ea3cf90ca45f97a2e4110fd5e4cac9e3b6b47c

Observation b06a2f11-c15f-4649-886d-57b2b22caade · outbound

This paper cites What's in a Name? Auditing Large Language Models for Race and Gender Bias.

Towards Effective Discrimination Testing for Generative AI What's in a Name? Auditing Large Language Models for Race and Gender Bias

Reference 23

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source=pdf_text observed=2026-08-10T23:08:44.794018Z digest=sha256:28b12559354a71610509cca68b17c9a48561fd28be7be8de75aa752afdf93188

Observation efee1d72-06e8-46be-9fbe-90126027717d · outbound

This paper cites Ruby Teaming: Improving Quality Diversity Search with Memory for Automated Red Teaming.

Towards Effective Discrimination Testing for Generative AI Ruby Teaming: Improving Quality Diversity Search with Memory for Automated Red Teaming

Reference 24

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source=pdf_text observed=2026-08-10T23:08:44.840047Z digest=sha256:40ca55d8037bf4166ea24c9c1389e401010910b0d9fcbf69c0bcf7c9b3dbe2a4

Observation 35f4f9b4-3aa7-4454-a51f-4493b6c3b9bf · outbound

This paper cites TrustAgent: Towards Safe and Trustworthy LLM-based Agents.

Towards Effective Discrimination Testing for Generative AI TrustAgent: Towards Safe and Trustworthy LLM-based Agents

Reference 26

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no resolver link, observed 2026-08-10T23:08:44.868696Z

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source=pdf_text observed=2026-08-10T23:08:44.868696Z digest=sha256:fed7afbe62f082a1b71390130e3bcede7524fdc08917f1007e302fad291b9418

Observation f9343a61-7c0a-4a5f-a6b4-f2a0062b5050 · outbound

This paper cites Automated Progressive Red Teaming.

Towards Effective Discrimination Testing for Generative AI Automated Progressive Red Teaming

Reference 27

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source=pdf_text observed=2026-08-10T23:08:44.875046Z digest=sha256:e2169f6a69fe4685b1f2270b1a1d680a81be452052d1f96deaa5dfe8cd8f2385

Observation c23a4b30-bca6-477a-984f-e73f601c26bd · outbound

This paper cites RewardBench: Evaluating Reward Models for Language Modeling.

Towards Effective Discrimination Testing for Generative AI RewardBench: Evaluating Reward Models for Language Modeling

Reference 28

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source=pdf_text observed=2026-08-10T23:08:44.881213Z digest=sha256:4c8e68bf77ee5512a6b88f0e36644289723ee1ed0bc706264c019e41e7d62d74

Observation c7658f5f-b9a9-4386-803c-169039fbba94 · outbound

This paper cites Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation.

Towards Effective Discrimination Testing for Generative AI Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation

Reference 30

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source=pdf_text observed=2026-08-10T23:08:44.908977Z digest=sha256:45c4fdc69c2713e4f86210103cc1725ddcb2e38f9089afa57bcbd0935eb89031

Observation 6093cf5d-27df-4080-ad14-8accbbd31cab · outbound

This paper cites Zemel, Kai-Wei Chang, Aram Galstyan, and Rahul Gupta.

Towards Effective Discrimination Testing for Generative AI Zemel, Kai-Wei Chang, Aram Galstyan, and Rahul Gupta

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.958343Z digest=sha256:2e543bb4dab89d4b8d2a8118eecdbe6c093e1db7355bc84ce4064583b6779978

Observation 1b344f11-9f7e-4c13-93af-79af775b229c · outbound

This paper cites GPT-4 Technical Report.

Towards Effective Discrimination Testing for Generative AI GPT-4 Technical Report

Reference 32

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source=pdf_text observed=2026-08-10T23:08:44.980102Z digest=sha256:20b98e84ec0e8653a7ea33d966e2e7c7e592367c21352c88dee562bf04d1dd47

Observation 53eb0d49-5da6-4535-904b-5ace80f5eb79 · outbound

This paper cites Red teaming language models with language models.

Towards Effective Discrimination Testing for Generative AI Red teaming language models with language models

Reference 33

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.987631Z digest=sha256:34255c50dc7c4dc0d3be94302091b972d66f7b2bdbda1e6285d03dd0f7930216

Observation aabfd4c0-59e7-463a-9b0e-e41b0a95a90e · outbound

This paper cites ZOLLO , N.

Towards Effective Discrimination Testing for Generative AI ZOLLO , N

Reference 35

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:45.000927Z digest=sha256:288e1d32b772058e1636586eae388252a8fdc95c6662d96f628a7e7823d5886e

Observation 4d013b7b-4243-4dd8-ab73-5baa13f66d23 · outbound

This paper cites AI and the Everything in the Whole Wide World Benchmark.

Towards Effective Discrimination Testing for Generative AI AI and the Everything in the Whole Wide World Benchmark

Reference 36

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source=pdf_text observed=2026-08-10T23:08:45.007232Z digest=sha256:24250d744bdb3234132e03e15b55c8903856944d85e27b0ab4f9adb8a16e1d84

Observation b56f97a4-27ab-4319-b62b-025adf577f81 · outbound

This paper cites Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval.

Towards Effective Discrimination Testing for Generative AI Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

Reference 37

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source=pdf_text observed=2026-08-10T23:08:45.013758Z digest=sha256:1436445373914aad18f5729c971b4a1cd6b1dd42bb59bf4cb1b02d5ce20059d9

Observation e2f0eef1-7b78-4339-a36a-499e667d4121 · outbound

This paper cites Style Over Substance: Evaluation Biases for Large Language Models.

Towards Effective Discrimination Testing for Generative AI Style Over Substance: Evaluation Biases for Large Language Models

Reference 38

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source=pdf_text observed=2026-08-10T23:08:45.056396Z digest=sha256:d6ff5839e7ad74f9baf70f684963ae41c8e53454c1779242861068839635110d

Observation da8fea35-815f-4301-8020-157607afa73f · outbound

This paper cites Bias in Generative AI.

Towards Effective Discrimination Testing for Generative AI Bias in Generative AI

Reference 39

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source=pdf_text observed=2026-08-10T23:08:45.093035Z digest=sha256:23588a8c4d8cedbc8134989ed70e49ba2af44263ad43b70b86c0ac54a6c06fbd

Observation ecb24f40-f36e-4719-b049-5fd1a8aff5c1 · outbound

This paper cites PersonalLLM: Tailoring LLMs to Individual Preferences.

Towards Effective Discrimination Testing for Generative AI PersonalLLM: Tailoring LLMs to Individual Preferences

Reference 40

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source=pdf_text observed=2026-08-10T23:08:45.099665Z digest=sha256:9ec439129cc49f8fe3416dc88f14679cfef96fc2148d726558366422141d23e5

Observation 0e581f22-6566-4b66-988b-03662e1ab684 · outbound

This paper cites To compute toxicity, we use the Detoxify model Hanu and Unitary team (2020).

Towards Effective Discrimination Testing for Generative AI To compute toxicity, we use the Detoxify model Hanu and Unitary team (2020)

Reference 43

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raw_fallback, observed 2026-08-10T23:08:45.995232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:45.121973Z digest=sha256:a888c5eb28bee94a2611b194cec5eb416bfacaed4cde1fbd7d74fcf4d41da4a6

Observation 44a97102-141b-4a2d-a53a-f922111f197f · outbound

This paper cites ZOLLO , N.

Towards Effective Discrimination Testing for Generative AI ZOLLO , N

Reference 44

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raw_fallback, observed 2026-08-10T23:08:45.976276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:45.205423Z digest=sha256:06a978e7b04bb0bfaf023dce810ee2971dcc8d48bf22fc0e8a95df09a754453b

Observation 26809750-fcce-49b9-9673-0a1ae94a4fec · outbound

This paper cites Appendix B.

Towards Effective Discrimination Testing for Generative AI Appendix B

Reference 144

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raw_fallback, observed 2026-08-10T23:08:46.149621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:45.106834Z digest=sha256:fd83bb326b93729706e732300b83e20c178357f87f649043e009a53075f30672

Observation d0c3ac21-48c2-4cef-8e38-02af4c7b047d · outbound

This paper cites Auditing the Use of Language Models to Guide Hiring Decisions.

Towards Effective Discrimination Testing for Generative AI Auditing the Use of Language Models to Guide Hiring Decisions

Reference 1968

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no resolver link, observed 2026-08-10T23:08:44.673837Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T23:08:44.673837Z digest=sha256:21e7f3fff95dd73dd0087306e7af3ad6979b57b98b9bb5be47630a29c521da14

Observation 696753ce-5899-4818-b339-960a317b456c · outbound

This paper cites Directive 2006/54/ec on the implementation of the principle of equal opportunities and equal treatment of men and women in matters of employment and occupation (recast),.

Towards Effective Discrimination Testing for Generative AI Directive 2006/54/ec on the implementation of the principle of equal opportunities and equal treatment of men and women in matters of employment and occupation (recast),

Reference 2000

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verified fuzzy
raw_fallback, observed 2026-08-10T23:08:46.688609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.430384Z digest=sha256:ad0954279492c7ac7051f1a8d62f87988a73165b097db27636a309c69d9ca778

Observation 29980607-0d8d-4f77-9b28-a3a3fcef0267 · outbound

This paper cites Easily accessible text-to- image generation amplifies demographic stereotypes at large scale.

Towards Effective Discrimination Testing for Generative AI Easily accessible text-to- image generation amplifies demographic stereotypes at large scale

Reference 2003

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verified fuzzy
raw_fallback, observed 2026-08-10T23:08:47.249516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.089089Z digest=sha256:a1d5f5f48372da67b23cff32350139d0b3b2dfbe8a9a48d74606cb94dde7b3bc

Observation e842c87d-1d20-477e-b31a-940af98aec17 · outbound

This paper cites Toxicchat: Unveiling hidden challenges of toxicity detection in real-world user-ai conversation.

Towards Effective Discrimination Testing for Generative AI Toxicchat: Unveiling hidden challenges of toxicity detection in real-world user-ai conversation

Reference 2004

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raw_fallback, observed 2026-08-10T23:08:46.394576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.887215Z digest=sha256:4100a0e044f3a6e503433ee7a9304bd177dfe20dc56aed97e1a9e7e9b3e1513d

Observation b40f2784-af29-4fbf-a6c9-6b976b92894d · outbound

This paper cites Directive 2000/78/ec establishing a general framework for equal treatment in employment and occupation,.

Towards Effective Discrimination Testing for Generative AI Directive 2000/78/ec establishing a general framework for equal treatment in employment and occupation,

Reference 2006

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verified fuzzy
raw_fallback, observed 2026-08-10T23:08:46.614791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.456276Z digest=sha256:fc81827ffa9d46faa39dfa641974bb3515eca31151145032ffc4c841619ba451

Observation 88516843-4c0e-48cf-99af-e9ad0cf645e4 · outbound

This paper cites an unresolved cited work.

Towards Effective Discrimination Testing for Generative AI Unresolved cited work

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T23:08:44.862387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:08:44.862387Z digest=sha256:1bd13c079f6e0c06319635f861360d90d719efcaa8a0d04735169490ea7f60a1

Observation a0e8e9bb-beca-4ef8-9e44-9432956902da · outbound

This paper cites Generative Discrimination: What Happens When Generative AI Exhibits Bias, and What Can Be Done About It.

Towards Effective Discrimination Testing for Generative AI Generative Discrimination: What Happens When Generative AI Exhibits Bias, and What Can Be Done About It

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-10T23:08:44.712997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:08:44.712997Z digest=sha256:cf0d374156b82599d81e1e80459d4ef280b2b3910c5e5a3005c382ce46d7eb18

Observation f93312af-f1e7-403e-8806-ea7b28151be5 · outbound

This paper cites Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell.

Towards Effective Discrimination Testing for Generative AI Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:08:47.267330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.078577Z digest=sha256:3b52ea95c38e17949bde95df372ec644490274d310b1889db00c04c37157e431

Observation 00e2ddb5-3d27-4472-8a64-62a4b5a27768 · outbound

This paper cites Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models.

Towards Effective Discrimination Testing for Generative AI Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:08:46.249130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.994488Z digest=sha256:5dd5daa5231e836ac214bac0e513e904cfd7a97b85c58897d297c8f87c2848cd

Observation 75fe4917-f4e1-4f47-8599-4e3b568a684a · outbound

This paper cites ZOLLO , N.

Towards Effective Discrimination Testing for Generative AI ZOLLO , N

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:08:47.005740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.103108Z digest=sha256:df4378e6427f3c3d990b76288610384d199e61f002135044f91a864e272ae432

Observation 6c642ce8-728d-4eac-98e1-d5e0aa782d9c · outbound

This paper cites FairMonitor: A Dual-framework for Detecting Stereotypes and Biases in Large Language Models.

Towards Effective Discrimination Testing for Generative AI FairMonitor: A Dual-framework for Detecting Stereotypes and Biases in Large Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T23:08:43.991185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:08:43.991185Z digest=sha256:cadc94d1c0f0a29483f2f67ab6641441aaf4d1971672a89d3da1b275438b5e4c

Observation 483d865e-757d-4955-8958-dbeb0855287e · outbound

This paper cites Leave-one-out unfairness.

Towards Effective Discrimination Testing for Generative AI Leave-one-out unfairness

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:08:47.028015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T23:08:44.096919Z digest=sha256:eefe6e8d8287e580323f9a5627d383a6c7d015bda4ae7188d94c4f89accd170f

Observation f37d80f9-d625-42cd-ae96-8c4f52ed40fa · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Towards Effective Discrimination Testing for Generative AI Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T23:08:44.040228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:08:44.040228Z digest=sha256:bd9f91fbf887c6716021f3e5ebe7b14c0811b8a2ea26c603a66a4ec653d5068d

Pith citing papers

No inbound Pith citation observations are available.