fairness.md

A5. Fairness

• [2024/08] Pro-Woman, Anti-Man? Identifying Gender Bias in Stance Detection
• [2024/08] Social Debiasing for Fair Multi-modal LLMs
• [2024/06] GenderAlign: An Alignment Dataset for Mitigating Gender Bias in Large Language Models
• [2024/05] FairMonitor: A Dual-framework for Detecting Stereotypes and Biases in Large Language Models
• [2024/03] Born With a Silver Spoon? Investigating Socioeconomic Bias in Large Language Models
• [2024/03] Protected group bias and stereotypes in Large Language Models
• [2024/03] Locating and Mitigating Gender Bias in Large Language Models
• [2024/03] Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework
• [2024/03] Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
• [2024/03] Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution
• [2024/03] "Flex Tape Can't Fix That": Bias and Misinformation in Edited Language Models
• [2024/03] Gender Bias in Large Language Models across Multiple Languages
• [2024/02] FairBelief - Assessing Harmful Beliefs in Language Models
• [2024/02] What's in a Name? Auditing Large Language Models for Race and Gender Bias
• [2024/02] Measuring Social Biases in Masked Language Models by Proxy of Prediction Quality
• [2024/02] Your Large Language Model is Secretly a Fairness Proponent and You Should Prompt it Like One
• [2024/02] Disclosure and Mitigation of Gender Bias in LLMs
• [2024/02] I Am Not Them: Fluid Identities and Persistent Out-group Bias in Large Language Models
• [2024/01] Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting
• [2024/01] Gender Bias in Machine Translation and The Era of Large Language Models
• [2024/01] Leveraging Biases in Large Language Models: "bias-kNN'' for Effective Few-Shot Learning
• [2024/01] Beyond the Surface: A Global-Scale Analysis of Visual Stereotypes in Text-to-Image Generation
• [2023/12] GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models
• [2023/11] Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models
• [2023/11] FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, Toxicity
• [2023/11] ROBBIE: Robust Bias Evaluation of Large Generative Language Models
• [2023/10] Im not Racist but...: Discovering Bias in the Internal Knowledge of Large Language Models
• [2023/10] Investigating the Fairness of Large Language Models for Predictions on Tabular Data
• [2023/10] Kelly is a Warm Person, Joseph is a Role Model: Gender Biases in LLM-Generated Reference Letters
• [2023/09] Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
• [2023/09] Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
• [2023/09] FairVLM: Mitigating Bias In Pre-Trained Vision-Language Models
• [2023/09] Finetuning Text-to-Image Diffusion Models for Fairness
• [2023/09] The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
• [2023/09] Bias and Fairness in Chatbots: An Overview
• [2023/09] Bias and Fairness in Large Language Models: A Survey
• [2023/09] People's Perceptions Toward Bias and Related Concepts in Large Language Models: A Systematic Review
• [2023/08] FairBench: A Four-Stage Automatic Framework for Detecting Stereotypes and Biases in Large Language Models
• [2023/08] Gender bias and stereotypes in Large Language Models
• [2023/07] Queer People are People First: Deconstructing Sexual Identity Stereotypes in Large Language Models
• [2023/06] Knowledge of cultural moral norms in large language models
• [2023/06] WinoQueer: A Community-in-the-Loop Benchmark for Anti-LGBTQ+ Bias in Large Language Models
• [2023/05] BiasAsker: Measuring the Bias in Conversational AI System
• [2023/05] Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
• [2023/05] Large Language Models are not Fair Evaluators
• [2023/05] Uncovering and Quantifying Social Biases in Code Generation
• [2022/09] Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis
• [2022/09] Moral Mimicry: Large Language Models Produce Moral Rationalizations Tailored to Political Identity
• [2022/05] Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts
• [2022/03] Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal
• [2021/04] Mitigating Political Bias in Language Models Through Reinforced Calibration
• [2021/02] Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models
• [2021/01] Persistent Anti-Muslim Bias in Large Language Models