Fairness

HirePeer: Impartial Peer-Assessed Hiring at Scale in Expert Crowdsourcing Markets AAAI 2020 How do fair decisions fare in long-term qualification? NeurIPS 2020 How to Solve Fair k-Center in Massive Data Models ICML 2020 Identifying and Correcting Label Bias in Machine Learning AISTATS 2020 Identifying and Measuring Annotator Bias Based on Annotators’ Demographic Characteristics EMNLP 2020 Identifying Model Weakness with Adversarial Examiner AAAI 2020 Identifying Spurious Correlations for Robust Text Classification EMNLP 2020 Impact of Politically Biased Data on Hate Speech Classification EMNLP 2020 Improving QA Generalization by Concurrent Modeling of Multiple Biases EMNLP 2020 Incorporating Interpretable Output Constraints in Bayesian Neural Networks NeurIPS 2020 Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations AAAI 2020 In Data We Trust: A Critical Analysis of Hate Speech Detection Datasets EMNLP 2020 Individual Calibration with Randomized Forecasting ICML 2020 Individual Fairness for k-Clustering ICML 2020 Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness IJCAI 2020 Integrating Ethics into the NLP Curriculum ACL 2020 Interdependencies of Gender and Race in Contextualized Word Embeddings COLING 2020 Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings ACL 2020 Intra-Processing Methods for Debiasing Neural Networks NeurIPS 2020 Invariant Representations through Adversarial Forgetting AAAI 2020 Investigating African-American Vernacular English in Transformer-Based Text Generation EMNLP 2020 Investigating Annotator Bias with a Graph-Based Approach EMNLP 2020 Investigating Gender Bias in Language Models Using Causal Mediation Analysis NeurIPS 2020 Investigating Sampling Bias in Abusive Language Detection EMNLP 2020 Investigating Societal Biases in a Poetry Composition System COLING 2020