Fairness

On Releasing Annotator-Level Labels and Information in Datasets EMNLP 2021 Optimized Score Transformation for Consistent Fair Classification JMLR 2021 OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings EMNLP 2021 Overparameterisation and worst-case generalisation: friend or foe? ICLR 2021 Post-processing for Individual Fairness NeurIPS 2021 Protecting the Protected Group: Circumventing Harmful Fairness AAAI 2021 Quantifying and Avoiding Unfair Qualification Labour in Crowdsourcing ACL 2021 RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ACL 2021 Reliability Testing for Natural Language Processing Systems ACL 2021 SCRUPLES: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes AAAI 2021 Selective Classification Can Magnify Disparities Across Groups ICLR 2021 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness ICLR 2021 Sociolectal Analysis of Pretrained Language Models EMNLP 2021 Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you? EMNLP 2021 Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets ACL 2021 Strategic Classification in the Dark ICML 2021 Sustainable Modular Debiasing of Language Models EMNLP 2021 Testing Group Fairness via Optimal Transport Projections ICML 2021 The Effect of Round-Trip Translation on Fairness in Sentiment Analysis EMNLP 2021 The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets AAAI 2021 Themis: A Fair Evaluation Platform for Computer Vision Competitions IJCAI 2021 Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers NAACL 2021 Towards a unified framework for fair and stable graph representation learning UAI 2021 Towards Automatic Bias Detection in Knowledge Graphs EMNLP 2021 Towards Fair and Transparent Algorithmic Systems IJCAI 2021