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Out-of-Distribution Generalization

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TitleStatusHype
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
GeoMix: Towards Geometry-Aware Data AugmentationCode0
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design—0
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
SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning—0
Face Reconstruction Transfer Attack as Out-of-Distribution GeneralizationCode0
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
Is Programming by Example solved by LLMs?—0
CTBENCH: A Library and Benchmark for Certified TrainingCode0
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation—0
Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks—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
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization—0
What Variables Affect Out-of-Distribution Generalization in Pretrained Models?—0
Automated Text Identification Using CNN and Training Dynamics—0
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural NetworksCode0
A separability-based approach to quantifying generalization: which layer is best?Code0
Invariant Risk Minimization Is A Total Variation ModelCode0
Cross-Domain Causal Preference Learning for Out-of-Distribution RecommendationCode0
An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics—0
On the Benefits of Over-parameterization for Out-of-Distribution Generalization—0
SYNAPSE: SYmbolic Neural-Aided Preference Synthesis Engine—0
IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History—0
Awakening Augmented Generation: Learning to Awaken Internal Knowledge of Large Language Models for Question AnsweringCode0
Early Period of Training Impacts Adaptation for Out-of-Distribution Generalization: An Empirical Study—0
Transfer Learning Beyond Bounded Density Ratios—0
Disentangling Policy from Offline Task Representation Learning via Adversarial Data AugmentationCode0
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness—0
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation—0
A Survey on Evaluation of Out-of-Distribution Generalization—0
Vision Transformers with Natural Language Semantics—0
A Neural Rewriting System to Solve Algorithmic Problems—0
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective—0
HYPO: Hyperspherical Out-of-Distribution GeneralizationCode0
On the Out-Of-Distribution Generalization of Multimodal Large Language Models—0
On Provable Length and Compositional GeneralizationCode0
Neural Language of Thought Models—0
Towards Understanding Variants of Invariant Risk Minimization through the Lens of CalibrationCode0
Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Survey—0
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization—0
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