distributional shift

Boosted Control Functions: Distribution Generalization and Invariance in Confounded Models JMLR 2026 Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments AAAI 2026 Gradual Uncertainty Refinement via Noise-Driven Curriculum: A Post-Hoc Meta-Model for Robust Uncertainty Quantification UAI 2026 Revealing Hidden Failure Modes in Chest X-ray Classification via Spectral Domain Analysis MIDL 2026 ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization ICLR 2025 Dynamic Uncertainty Estimation for Offline Reinforcement Learning AAAI 2025 From Distributional to Overton Pluralism: Investigating Large Language Model Alignment NAACL 2025 How to Synthesize Text Data without Model Collapse? ICML 2025 MARS: Benchmarking the Metaphysical Reasoning Abilities of Language Models with a Multi-task Evaluation Dataset ACL 2025 The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret ICML 2025 TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram ICLR 2025 Causal Action Influence Aware Counterfactual Data Augmentation ICML 2024 Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning ICLR 2024 Distributionally Robust Model-based Reinforcement Learning with Large State Spaces AISTATS 2024 Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes NeurIPS 2024 Enhancing Distributional Stability among Sub-populations AISTATS 2024 Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise NeurIPS 2024 Limitations of Face Image Generation AAAI 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NeurIPS 2024 Not all distributional shifts are equal: Fine-grained robust conformal inference ICML 2024 Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners ICML 2024 Robust agents learn causal world models ICLR 2024 TimeX++: Learning Time-Series Explanations with Information Bottleneck ICML 2024 Auxiliary Losses for Learning Generalizable Concept-based Models NeurIPS 2023 Bi-Level Offline Policy Optimization with Limited Exploration NeurIPS 2023