SOTAVerified

Out-of-Distribution Generalization

Papers

Showing 150 of 516 papers

TitleStatusHype
LIMO: Less is More for ReasoningCode5
LORE: Lagrangian-Optimized Robust Embeddings for Visual EncodersCode4
Deep Residual Learning for Image RecognitionCode4
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-ExpertsCode3
A Hard-to-Beat Baseline for Training-free CLIP-based AdaptationCode2
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to AdaptationCode2
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and TransportationCode2
UnIVAL: Unified Model for Image, Video, Audio and Language TasksCode2
Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing ModelCode2
Big Transfer (BiT): General Visual Representation LearningCode2
Learning Causally Invariant Representations for Out-of-Distribution Generalization on GraphsCode2
Learning Transferable Visual Models From Natural Language SupervisionCode2
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timeCode2
Entity-Based Knowledge Conflicts in Question AnsweringCode1
EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for ElectromyographyCode1
Environment-Aware Dynamic Graph Learning for Out-of-Distribution GeneralizationCode1
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution GeneralizationCode1
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
Domain-Specific Risk Minimization for Out-of-Distribution GeneralizationCode1
Environment Inference for Invariant LearningCode1
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement LearningCode1
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case GeneralizationCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein DesignCode1
Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive TasksCode1
Dog-IQA: Standard-guided Zero-shot MLLM for Mix-grained Image Quality AssessmentCode1
A Brief Introduction to Causal Inference in Machine LearningCode1
An Empirical Study of Training Self-Supervised Vision TransformersCode1
Adapting to Distribution Shift by Visual Domain Prompt GenerationCode1
Empirical Study of PEFT techniques for Winter Wheat SegmentationCode1
Diverse Weight Averaging for Out-of-Distribution GeneralizationCode1
Disentangled Generative Models for Robust Prediction of System DynamicsCode1
Designing Network Design SpacesCode1
Distilling Large Vision-Language Model with Out-of-Distribution GeneralizabilityCode1
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?Code1
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic AugmentationCode1
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge GraphsCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
Causal Transportability for Visual RecognitionCode1
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-Of-Distribution GeneralizationCode1
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
Discovering environments with XRMCode1
Unleashing the Power of Graph Data Augmentation on Covariate Distribution ShiftCode1
Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language InferenceCode1
Broken Neural Scaling LawsCode1
Deep Stable Learning for Out-Of-Distribution GeneralizationCode1
Contextual Vision Transformers for Robust Representation LearningCode1
Collaboration! Towards Robust Neural Methods for Routing ProblemsCode1
Geometric Deep Learning for Structure-Based Drug Design: A SurveyCode1
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies OthersCode1
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