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Out-of-Distribution Generalization

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TitleStatusHype
Invariant Risk Minimization Is A Total Variation ModelCode0
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-ExpertsCode3
A separability-based approach to quantifying generalization: which layer is best?Code0
In-Context Symbolic Regression: Leveraging Large Language Models for Function DiscoveryCode1
Cross-Domain Causal Preference Learning for Out-of-Distribution RecommendationCode0
The Causal Chambers: Real Physical Systems as a Testbed for AI MethodologyCode1
N-Agent Ad Hoc TeamworkCode1
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
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated ExpertsCode1
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
Improving out-of-distribution generalization in graphs via hierarchical semantic environmentsCode1
Vision Transformers with Natural Language Semantics—0
A Neural Rewriting System to Solve Algorithmic Problems—0
Graph Out-of-Distribution Generalization via Causal InterventionCode1
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
A Hard-to-Beat Baseline for Training-free CLIP-based AdaptationCode2
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
Trapped in texture bias? A large scale comparison of deep instance segmentationCode1
InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization—0
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs—0
Regularized Parameter Uncertainty for Improving Generalization in Reinforcement Learning—0
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge GraphsCode1
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift—0
Mixture Data for Training Cannot Ensure Out-of-distribution Generalization—0
Learning to Reweight for Graph Neural Network—0
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution GeneralizationCode1
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction—0
Holistic chemical evaluation reveals pitfalls in reaction prediction modelsCode0
Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression—0
Class Distribution Shifts in Zero-Shot Learning: Learning Robust RepresentationsCode0
Towards out-of-distribution generalization in large-scale astronomical surveys: robust networks learn similar representations—0
LanGWM: Language Grounded World Model—0
ArGue: Attribute-Guided Prompt Tuning for Vision-Language Models—0
Environment-Aware Dynamic Graph Learning for Out-of-Distribution GeneralizationCode1
In-context Learning Generalizes, But Not Always Robustly: The Case of SyntaxCode0
Generalization in medical AI: a perspective on developing scalable models—0
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