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Machine Learning
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Fairness
3337 directly classified papers
Papers per year
2011: 1
2013: 3
2014: 2
2016: 6
2017: 30
2018: 65
2019: 182
2020: 239
2021: 373
2022: 456
2023: 533
2024: 648
2025: 644
2026: 155
Papers
DLAMA: A Framework for Curating Culturally Diverse Facts for Probing the Knowledge of Pretrained Language Models
ACL 2023
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning
NIPS 2023
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
ICML 2023
Data Feedback Loops: Model-driven Amplification of Dataset Biases
ICML 2023
Gender-tuning: Empowering Fine-tuning for Debiasing Pre-trained Language Models
ACL 2023
Contextual Reliability: When Different Features Matter in Different Contexts
ICML 2023
Group Robust Classification Without Any Group Information
NIPS 2023
DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
NIPS 2023
Trading-off price for data quality to achieve fair online allocation
NIPS 2023
Debiasing should be Good and Bad: Measuring the Consistency of Debiasing Techniques in Language Models
ACL 2023
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
NIPS 2023
Bias Beyond English: Counterfactual Tests for Bias in Sentiment Analysis in Four Languages
ACL 2023
FairLISA: Fair User Modeling with Limited Sensitive Attributes Information
NIPS 2023
Reducing Sensitivity on Speaker Names for Text Generation from Dialogues
ACL 2023
Algorithmics of Egalitarian versus Equitable Sequences of Committees
IJCAI 2023
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions
NIPS 2023
Seeing is not always believing: Benchmarking Human and Model Perception of AI-Generated Images
NIPS 2023
Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation
WACV 2023
Misclassifications of Contact Lens Iris PAD Algorithms: Is It Gender Bias or Environmental Conditions?
WACV 2023
FACTS: First Amplify Correlations and Then Slice to Discover Bias
ICCV 2023
Certification of Distributional Individual Fairness
NIPS 2023
H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
NIPS 2023
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
NIPS 2023
Delegated Classification
NIPS 2023
Auditing Fairness by Betting
NIPS 2023
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