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Fairness

3337 directly classified papers

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Papers

Viable Threat on News Reading: Generating Biased News Using Natural Language Models EMNLP 2020
FACT: A Diagnostic for Group Fairness Trade-offs ICML 2020
Feature Noise Induces Loss Discrepancy Across Groups ICML 2020
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing ICML 2020
Data preprocessing to mitigate bias: A maximum entropy based approach ICML 2020
Crossing the Line: Where do Demographic Variables Fit into Humor Detection? ACL 2020
Optimized Score Transformation for Fair Classification AISTATS 2020
Model-Agnostic Counterfactual Explanations for Consequential Decisions AISTATS 2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency NIPS 2020
HINT3: Raising the bar for Intent Detection in the Wild EMNLP 2020
An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference EMNLP 2020
Automatically Identifying Gender Issues in Machine Translation using Perturbations EMNLP 2020
Identifying Model Weakness with Adversarial Examiner AAAI 2020
Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning AAAI 2020
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning EMNLP 2020
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies NIPS 2020
Fairness with Overlapping Groups; a Probabilistic Perspective NIPS 2020
Robust Optimization for Fairness with Noisy Protected Groups NIPS 2020
Neutralizing Self-Selection Bias in Sampling for Sortition NIPS 2020
Fair regression with Wasserstein barycenters NIPS 2020
Fair Performance Metric Elicitation NIPS 2020
Metric-Free Individual Fairness in Online Learning NIPS 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses NIPS 2020
AI at the Margins: Data, Decisions, and Inclusive Social Impact IJCAI 2019
Tanbih: Get To Know What You Are Reading EMNLP 2019