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Out-of-Distribution Generalization

Papers

Showing 101150 of 516 papers

TitleStatusHype
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
Improving robustness against common corruptions by covariate shift adaptationCode1
AugMix: A Simple Data Processing Method to Improve Robustness and UncertaintyCode1
Dataset Cartography: Mapping and Diagnosing Datasets with Training DynamicsCode1
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded AugmentationsCode1
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic AugmentationCode1
Invariance Principle Meets Information Bottleneck for Out-of-Distribution GeneralizationCode1
Invariant Risk MinimizationCode1
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?Code1
Environment Inference for Invariant LearningCode1
Entity-Based Knowledge Conflicts in Question AnsweringCode1
Deep Stable Learning for Out-Of-Distribution GeneralizationCode1
A Brief Introduction to Causal Inference in Machine LearningCode1
Is a Modular Architecture Enough?Code1
Delving Deep into the Generalization of Vision Transformers under Distribution ShiftsCode1
Designing Network Design SpacesCode1
LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model MergingCode1
Just Train Twice: Improving Group Robustness without Training Group InformationCode1
Diverse Weight Averaging for Out-of-Distribution GeneralizationCode1
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
Discovering environments with XRMCode1
Learning Divergence Fields for Shift-Robust Graph RepresentationsCode1
Disentangled Generative Models for Robust Prediction of System DynamicsCode1
Learning Representations that Support Robust Transfer of PredictorsCode1
Distilling Large Vision-Language Model with Out-of-Distribution GeneralizabilityCode1
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasksCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
Linear unit-tests for invariance discoveryCode1
Looking Inward: Language Models Can Learn About Themselves by IntrospectionCode1
Environment-Aware Dynamic Graph Learning for Out-of-Distribution GeneralizationCode1
Masked Autoencoders Are Scalable Vision LearnersCode1
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?Code1
Dog-IQA: Standard-guided Zero-shot MLLM for Mix-grained Image Quality AssessmentCode1
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution GeneralizationCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to GeneralizeCode1
Domain-Specific Risk Minimization for Out-of-Distribution GeneralizationCode1
A Policy-Guided Imitation Approach for Offline Reinforcement LearningCode1
Fishr: Invariant Gradient Variances for Out-of-Distribution GeneralizationCode1
FM2S: Towards Spatially-Correlated Noise Modeling in Zero-Shot Fluorescence Microscopy Image DenoisingCode1
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge GraphsCode1
From Local Details to Global Context: Advancing Vision-Language Models with Attention-Based SelectionCode1
EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for ElectromyographyCode1
Empirical Study of PEFT techniques for Winter Wheat SegmentationCode1
Unleashing the Power of Graph Data Augmentation on Covariate Distribution ShiftCode1
Generative Interventions for Causal LearningCode1
Gradient Starvation: A Learning Proclivity in Neural NetworksCode1
Optimizing Relevance Maps of Vision Transformers Improves RobustnessCode1
CARE: a Benchmark Suite for the Classification and Retrieval of EnzymesCode1
Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic MathematicsCode1
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