out-of-distribution generalization

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets NeurIPS 2023 Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the “What” and Focus on the “How”! ACL 2023 Improving Bias Mitigation through Bias Experts in Natural Language Understanding EMNLP 2023 Improving Generalization With Domain Convex Game CVPR 2023 Improving Out-of-distribution Generalization with Indirection Representations ICLR 2023 Improving the robustness of NLI models with minimax training ACL 2023 Invariant Learning via Probability of Sufficient and Necessary Causes NeurIPS 2023 Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization NeurIPS 2023 Learning Conditional Generative Models for Phase Retrieval JMLR 2023 Learning Invariant Molecular Representation in Latent Discrete Space NeurIPS 2023 Learning to Extrapolate: A Transductive Approach ICLR 2023 Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning ICCV 2023 Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds ICLR 2023 MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters ICCV 2023 Measure the Predictive Heterogeneity ICLR 2023 Mind the Label Shift of Augmentation-Based Graph OOD Generalization CVPR 2023 Mitigating and Evaluating Static Bias of Action Representations in the Background and the Foreground ICCV 2023 Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization ICLR 2023 Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization ACL 2023 Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization ICML 2023 Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal ICML 2023 Neural Algorithmic Reasoning with Causal Regularisation ICML 2023 Neural Algorithmic Reasoning Without Intermediate Supervision NeurIPS 2023 Neural Image Compression: Generalization, Robustness, and Spectral Biases NeurIPS 2023 On the Adversarial Robustness of Out-of-distribution Generalization Models NeurIPS 2023