bias detection

Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology ICML 2022 Using Natural Sentence Prompts for Understanding Biases in Language Models NAACL 2022 VisCUIT: Visual Auditor for Bias in CNN Image Classifier CVPR 2022 What Do You See in this Patient? Behavioral Testing of Clinical NLP Models NAACL 2022 An Overview of Fairness in Data – Illuminating the Bias in Data Pipeline EACL 2021 Assessing Gender Bias in Wikipedia: Inequalities in Article Titles ACL 2021 A Survey of Race, Racism, and Anti-Racism in NLP ACL 2021 Certifying Robustness to Programmable Data Bias in Decision Trees NeurIPS 2021 Competency Problems: On Finding and Removing Artifacts in Language Data EMNLP 2021 Debiasing Methods in Natural Language Understanding Make Bias More Accessible EMNLP 2021 DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces EACL 2021 Detecting Cross-Geographic Biases in Toxicity Modeling on Social Media EMNLP 2021 Discover the Unknown Biased Attribute of an Image Classifier ICCV 2021 Eliciting Bias in Question Answering Models through Ambiguity EMNLP 2021 Evaluation of Summarization Systems across Gender, Age, and Race EMNLP 2021 From Toxicity in Online Comments to Incivility in American News: Proceed with Caution EACL 2021 Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives ACL 2021 Guiding Principles for Participatory Design-inspired Natural Language Processing ACL 2021 Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies EMNLP 2021 HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection AAAI 2021 How do people interact with biased text prediction models while writing? EACL 2021 Improving Policing with Natural Language Processing ACL 2021 Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources EMNLP 2021 Leveraging Community and Author Context to Explain the Performance and Bias of Text-Based Deception Detection Models NAACL 2021 Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models EMNLP 2021