Gender Bias in Language Models

Ask about this topic

Overview

This field studies how gender cues shape language models’ representations, predictions, and generated text, with consequences for settings such as hiring, healthcare, translation, and user interaction. Researchers use counterfactual prompts, curated benchmarks such as BBQ and StereoSet, real-world tasks, and analyses of model representations to detect bias across languages, cultures, and modalities. Mitigation approaches include counterfactual data augmentation, fine-tuning and adversarial learning, representation editing, and inference-time steering. A central tension is that fairer outputs do not necessarily remove encoded associations, and interventions can affect factual knowledge, task performance, or fairness across contexts and groups.

Latest papers

CardsList

66 papers11 papers in the last four weeks, up 175% on the four weeks before. 0.1% of all new papers.

  1. Position: LLMs Must Use Functor-Based and RAG-Driven Bias Mitigation for Fairness

    Mar 7, 2026Ravi Ranjan, Utkarsh Grover, Agorista PolyzouSocial Bias in Language ModelsDemographic Bias in Language Models

    Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, FL 33199 · College of Engineering, University of South Florida, Tampa, FL 33620

  2. Intra-Fairness Dynamics: The Bias Spillover Effect in Targeted LLM Alignment

    Feb 18, 2026Eva Paraschou, Line Harder Clemmensen, Sneha DasLLM AlignmentLanguage Model Bias Evaluation

    Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Lyngby, Denmark · Department of Mathematical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark

  3. Robust Bias Evaluation with FilBBQ: A Filipino Bias Benchmark for Question-Answering Language Models

    Feb 16, 2026Lance Calvin Lim Gamboa, Yue Feng, Mark LeeSocial Bias in Language ModelsLanguage Model Bias Evaluation

    School of Computer Science, University of Birmingham · Department of Information Systems and Computer Science, Ateneo de Manila University

  4. Evaluating Implicit Biases in LLM Reasoning through Logic Grid Puzzles

    Nov 8, 2025Fatima Jahara, Mark Dredze, Sharon LevyGender Bias in Language ModelsLanguage Model Bias Evaluation

    Rutgers University · Johns Hopkins University

  5. Man Made Language Models? Evaluating LLMs' Perpetuation of Masculine Generics Bias

    Feb 14, 2025Enzo Doyen, Amalia TodirascuGender Bias in Language ModelsLanguage Model Bias Evaluation

    University of Strasbourg

  6. General Phrase Debiaser: Debiasing Masked Language Models at a Multi-Token Level

    Nov 23, 2023Bingkang Shi, Xiaodan Zhang, Dehan Kong +4Gender Bias in Language ModelsDebiased ML

    Chinese Academy of Sciences, Institute of Information Engineering, Beijing 100093, China · Alibaba Group, Alibaba Artificial Intelligence Governance Laboratory, Beijing, China · University of Bristol, Department of Electrical and Electronic Engineering, Bristol, BS8 1UB, UK