bias

Accelerating Unbiased LLM Evaluation via Synthetic Feedback ICML 2025 Adaptive Sample Sharing for Multi Agent Linear Bandits ICML 2025 Agnostic Learning of Arbitrary ReLU Activation under Gaussian Marginals COLT 2025 Debiasing Mini-Batch Quadratics for Applications in Deep Learning ICLR 2025 Fair Clustering: A Causal Perspective CLeaR 2025 Focus On This, Not That! Steering LLMs with Adaptive Feature Specification ICML 2025 Functional Alignment Can Mislead: Examining Model Stitching ICML 2025 Implicit degree bias in the link prediction task ICML 2025 Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs ICML 2025 Position: Generative AI Regulation Can Learn from Social Media Regulation ICML 2025 Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It ICML 2025 Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies ICML 2025 Representative Language Generation ICML 2025 Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation ICML 2025 Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up ICML 2025 Sharp bounds on aggregate expert error ALT 2025 TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems ICML 2025 Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods ICML 2025 Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance ICML 2024 Centralized Selection with Preferences in the Presence of Biases ICML 2024 Constructing Concept-based Models to Mitigate Spurious Correlations with Minimal Human Effort ECCV 2024 Debiasing surgeon: fantastic weights and how to find them ECCV 2024 Evaluating Model Bias Requires Characterizing its Mistakes ICML 2024 Feature Importance Disparities for Data Bias Investigations ICML 2024 Minimum Norm Interpolation Meets The Local Theory of Banach Spaces ICML 2024