Fairness

H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets NeurIPS 2023 How Far Can It Go? On Intrinsic Gender Bias Mitigation for Text Classification EACL 2023 How people talk about each other: Modeling Generalized Intergroup Bias and Emotion EACL 2023 How to address monotonicity for model risk management? ICML 2023 How to Construct Perfect and Worse-than-Coin-Flip Spoofing Countermeasures: A Word of Warning on Shortcut Learning Interspeech 2023 HRS-Bench: Holistic, Reliable and Scalable Benchmark for Text-to-Image Models ICCV 2023 Human-AI Collaboration in Recruitment and Selection IJCAI 2023 Human-Guided Fair Classification for Natural Language Processing ICLR 2023 Human Preference Score: Better Aligning Text-to-Image Models with Human Preference ICCV 2023 IAEval: A Comprehensive Evaluation of Instance Attribution on Natural Language Understanding EMNLP 2023 IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models EMNLP 2023 Identification of Systematic Errors of Image Classifiers on Rare Subgroups ICCV 2023 Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model EMNLP 2023 Identifying Selection Bias from Observational Data AAAI 2023 Improved Approximation for Fair Correlation Clustering AISTATS 2023 Improving Bias Mitigation through Bias Experts in Natural Language Understanding EMNLP 2023 Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting EMNLP 2023 Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues CVPR 2023 Improving Fairness in Information Exposure by Adding Links AAAI 2023 Improving Fair Training under Correlation Shifts ICML 2023 Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting ACL 2023 Improving Robust Fariness via Balance Adversarial Training AAAI 2023 Incentivizing Recourse through Auditing in Strategic Classification IJCAI 2023 In-Context Impersonation Reveals Large Language Models' Strengths and Biases NeurIPS 2023 In-Depth Look at Word Filling Societal Bias Measures EACL 2023