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Out-of-Distribution Generalization

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TitleStatusHype
DICS: Find Domain-Invariant and Class-Specific Features for Out-of-Distribution Generalization—0
VFA: Vision Frequency Analysis of Foundation Models and HumanCode0
H-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus BenchmarkCode1
NeuralOOD: Improving Out-of-Distribution Generalization Performance with Brain-machine Fusion Learning Framework—0
Out-of-distribution generalization via composition: a lens through induction heads in TransformersCode0
Predicting Long-Term Allograft Survival in Liver Transplant RecipientsCode0
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization—0
Label Augmentation for Neural Networks Robustness—0
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution GeneralizationCode0
Robust Simultaneous Multislice MRI Reconstruction Using Deep Generative PriorsCode0
Weighted Risk Invariance: Domain Generalization under Invariant Feature ShiftCode0
Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning—0
LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with Class TaxonomiesCode1
Distilling Vision-Language Foundation Models: A Data-Free Approach via Prompt Diversification—0
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial RepresentationsCode0
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein DesignCode1
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design—0
GeoMix: Towards Geometry-Aware Data AugmentationCode0
Improving Graph Out-of-distribution Generalization on Real-world Data—0
Adaptive Prediction Ensemble: Improving Out-of-Distribution Generalization of Motion Forecasting—0
Deciphering the Role of Representation Disentanglement: Investigating Compositional Generalization in CLIP ModelsCode0
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and TransportationCode2
SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning—0
Face Reconstruction Transfer Attack as Out-of-Distribution GeneralizationCode0
CARE: a Benchmark Suite for the Classification and Retrieval of EnzymesCode1
Perks and Pitfalls of Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs—0
Deep Temporal Deaggregation: Large-Scale Spatio-Temporal Generative Models—0
Insect Identification in the Wild: The AMI DatasetCode0
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex—0
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of AugmentationCode0
Exploring the Benefits of Vision Foundation Models for Unsupervised Domain AdaptationCode1
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant LearningCode1
Is Programming by Example solved by LLMs?—0
How Far Can Transformers Reason? The Globality Barrier and Inductive ScratchpadCode1
CTBENCH: A Library and Benchmark for Certified TrainingCode0
Learning Divergence Fields for Shift-Robust Graph RepresentationsCode1
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to GeneralizeCode1
Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks—0
Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasksCode1
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation—0
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift—0
Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data—0
Causal-aware Graph Neural Architecture Search under Distribution Shifts—0
Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning—0
What Variables Affect Out-of-Distribution Generalization in Pretrained Models?—0
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization—0
Automated Text Identification Using CNN and Training Dynamics—0
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural NetworksCode0
A Brief Introduction to Causal Inference in Machine LearningCode1
Adapting to Distribution Shift by Visual Domain Prompt GenerationCode1
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