FairPy: A Toolkit for Evaluation of Prediction Biases and their Mitigation in Large Language Models
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Abstract (arXiv)
Recent studies have demonstrated that large pretrained language models (LLMs) such as BERT and GPT-2 exhibit biases in token prediction, often inherited from the data distributions present in their training corpora. In response, a number of mathematical frameworks have been proposed to quantify, identify, and mitigate these the likelihood of biased token predictions. In this paper, we present a comprehensive survey of such techniques tailored towards widely used LLMs such as BERT, GPT-2, etc. We additionally introduce Fairpy, a modular and extensible toolkit that provides plug-and-play interfaces for integrating these mathematical tools, enabling users to evaluate both pretrained and custom language models. Fairpy supports the implementation of existing debiasing algorithms. The toolkit is open-source and publicly available at: hrefhttps://github.com/HrishikeshVish/Fairpyhttps://github.com/HrishikeshVish/Fairpy
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 23 of its 31 references that are in the map. First posted on arXiv 10 Feb 2023.
Builds on
23 of 31 references.
References · 23
- 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
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- 2020Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biasescited by 167
11 more
- 2018Reducing Gender Bias in Abusive Language Detectioncited by 152
- 2021RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Modelscited by 149
- 2021Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Modelscited by 141
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Citing papers per year: 2023: 2; 2024: 2; 2025: 1.
5 papers.
- 2023Challenges and Applications of Large Language Modelscited by 251
- 2024Evaluating Gender Bias in Large Language Models via Chain-of-Thought Promptingcited by 49
- 2023Bias and Fairness in Chatbots: An Overviewcited by 20
- 2024A Survey on Responsible Generative AI: What to Generate and What Notcited by 8
- 2025How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Modelscited by 0
- 2025How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models10 Nov 2025
- 2024A Survey on Responsible Generative AI: What to Generate and What Not8 Apr 2024
- 2024Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting28 Jan 2024
- 2023Bias and Fairness in Chatbots: An Overview16 Sep 2023
- 2023Challenges and Applications of Large Language Models19 Jul 2023