mlsanityData to 7 Oct 2026

Fairness in Large Language Models in Three Hours

arXiv 2408.00992 ↗First posted 2 Aug 2024cs.CL cs.LGcited by 7

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Abstract (arXiv)

Large Language Models (LLMs) have demonstrated remarkable success across various domains but often lack fairness considerations, potentially leading to discriminatory outcomes against marginalized populations. Unlike fairness in traditional machine learning, fairness in LLMs involves unique backgrounds, taxonomies, and fulfillment techniques. This tutorial provides a systematic overview of recent advances in the literature concerning fair LLMs, beginning with real-world case studies to introduce LLMs, followed by an analysis of bias causes therein. The concept of fairness in LLMs is then explored, summarizing the strategies for evaluating bias and the algorithms designed to promote fairness. Additionally, resources for assessing bias in LLMs, including toolkits and datasets, are compiled, and current research challenges and open questions in the field are discussed. The repository is available at urlhttps://github.com/LavinWong/Fairness-in-Large-Language-Models.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 35 of its 50 references that are in the map. First posted on arXiv 2 Aug 2024.

Builds on

35 of 50 references.

References · 35

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  2. 2020Language Models are Few-Shot Learnerscited by 32,199
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  4. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
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  9. 2018Gender Bias in Coreference Resolutioncited by 438
  10. 2021BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generationcited by 410
  11. 2021Persistent Anti-Muslim Bias in Large Language Modelscited by 376
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23 more
  1. 2023Gender bias and stereotypes in Large Language Modelscited by 185
  2. 2019Reducing Sentiment Bias in Language Models via Counterfactual Evaluationcited by 148
  3. 2018Aequitas: A Bias and Fairness Audit Toolkitcited by 145
  4. 2023Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendationcited by 113
  5. 2021Sustainable Modular Debiasing of Language Modelscited by 98
  6. 2021Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translationcited by 62
  7. 2024Fairness in Large Language Models: A Taxonomic Surveycited by 57
  8. 2023TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Modelscited by 56
  9. 2023BiasAsker: Measuring the Bias in Conversational AI Systemcited by 52
  10. 2024Evaluating Gender Bias in Large Language Models via Chain-of-Thought Promptingcited by 49
  11. 2021Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgettingcited by 34
  12. 2024History, Development, and Principles of Large Language Models-An Introductory Surveycited by 30
  13. 2022Text Style Transfer for Bias Mitigation using Masked Language Modelingcited by 27
  14. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 27
  15. 2023Fairness of ChatGPTcited by 19
  16. 2023DUnE: Dataset for Unified Editingcited by 19
  17. 2024Few-Shot Fairness: Unveiling LLM's Potential for Fairness-Aware Classificationcited by 18
  18. 2024Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutionscited by 17
  19. 2023Queer People are People First: Deconstructing Sexual Identity Stereotypes in Large Language Modelscited by 13
  20. 2023Preventing Discriminatory Decision-making in Evolving Data Streamscited by 12
  21. 2023Individual Fairness under Uncertaintycited by 11
  22. 2023Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societiescited by 11
  23. 2024Fairness Definitions in Language Models Explainedcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 1.

7 papers.

  1. 2024Bias in Large Language Models: Origin, Evaluation, and Mitigationcited by 77
  2. 2025Digital Forensics in the Age of Large Language Modelscited by 10
  3. 2025Simulating a Bias Mitigation Scenario in Large Language Modelscited by 4
  4. 2025AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Modelscited by 3
  5. 2025Detection, Classification, and Mitigation of Gender Bias in Large Language Modelscited by 1
  6. 2025It's complicated. The relationship of algorithmic fairness and non-discrimination provisions for high-risk systems in the EU AI Actcited by 0
  7. 2026Fair on the Surface? Benchmarking Hidden-Output Fairness Gaps in LLM Recommenderscited by 0