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Fairness

3337 directly classified papers

Papers per year

Papers

Does Question Really Matter? The Attribution of Answer Bias in LLM Evaluation AAAI 2026

Addressing Polarization and Unfairness in Performative Prediction AAAI 2026

Fair Bayesian Data Selection via Generalized Discrepancy Measures AAAI 2026

De-Speakerizing Accented ASR: Measuring and Mitigating Speaker Entanglement for Fair, Reliable Recognition AAAI 2026

Fairness in Repeated Matching: A Maximin Perspective AAAI 2026

Games of Representation: Developing Card-Based Activities to Teach About Representation and Bias in AI Datasets AAAI 2026

Are All Marine Species Created Equal? Performance Disparities in Underwater Object Detection WACV 2026

Conversational AI for Social Good (CAI4SG): An Overview of Emerging Trends, Applications, and Challenges AAAI 2026

BAFIS: Dataset + Framework to Assess Occupational Bias and Human Preference in Modern Text-to-image Models WACV 2026

How I Met Your Bias: Investigating Bias Amplification in Diffusion Models WACV 2026

Lose Your Self (LoYS): An Adversarial Entropy-based Unsupervised Approach for Model Debiasing WACV 2026

LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users AAAI 2026

Inequality in the Age of Pseudonymity AAAI 2026

Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images AAAI 2026

DP-NCB: Privacy Preserving Fair Bandits AAAI 2026

Decomposing Direct and Indirect Biases in Linear Models Under Demographic Parity Constraint AAAI 2026

FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness AAAI 2026

OursFed: Provable Group Fairness-Aware Federated Learning Against Distrust and Fragility AAAI 2026

Bayes-Optimal Fair Classification with Multiple Sensitive Features AAAI 2026

FairGC: Fostering Individual and Group Fairness for Deep Graph Clustering AAAI 2026

Fairness-Aware Design for Contextual Experiments: Guaranteeing Reliability and Equity in Heterogeneous Subgroups AAAI 2026

Fair Domain Generalization: An Information-Theoretic View AAAI 2026

Fair Model-based Clustering AAAI 2026

Beyond Binary Erasure: Soft-Weighted Unlearning for Fairness and Robustness AAAI 2026

Matrix Editing Meets Fair Clustering: Parameterized Algorithms and Complexity AAAI 2026