ood generalization

Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning AAAI 2026 Causality Inspired Federated Learning for OOD Generalization ICML 2025 Enhancing Graph Invariant Learning from a Negative Inference Perspective ICML 2025 Explaining Domain Shifts in Language: Concept Erasing for Interpretable Image Classification CVPR 2025 Graph OOD Detection via Plug-and-Play Energy-based Evaluation and Propagation IJCAI 2025 LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models ICML 2025 OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable? ICML 2025 OS-ATLAS: Foundation Action Model for Generalist GUI Agents ICLR 2025 AHA: Human-Assisted Out-of-Distribution Generalization and Detection NeurIPS 2024 Bridging OOD Detection and Generalization: A Graph-Theoretic View NeurIPS 2024 CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection ICML 2024 Dissecting the Failure of Invariant Learning on Graphs NeurIPS 2024 Domain Invariant Learning for Gaussian Processes and Bayesian Exploration AAAI 2024 InstructEdit: Instruction-Based Knowledge Editing for Large Language Models IJCAI 2024 Out-Of-Distribution Detection with Diversification (Provably) NeurIPS 2024 The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection NeurIPS 2024 Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights NeurIPS 2024 What Variables Affect Out-of-Distribution Generalization in Pretrained Models? NeurIPS 2024 Flatness-Aware Minimization for Domain Generalization ICCV 2023 Free Lunch for Domain Adversarial Training: Environment Label Smoothing ICLR 2023 What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? ICML 2023 Learning Causal Semantic Representation for Out-of-Distribution Prediction NeurIPS 2021