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Distribution Shift

196 papers

Papers per year

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Papers

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance ACL 2026
LLMs for Now, Fine-Tuning for Later: An Ensemble Approach to Data Drift in Domain-Specific Tasks ACL 2026
Is Exchangeability better than I.I.D. to handle Data Distribution Shifts while Pooling Data for Data-scarce Medical image segmentation? MIDL 2026
Beyond Discrepancy: A Closer Look at the Theory of Distribution Shift ALT 2026
Efficient and Provable Algorithms for Covariate Shift ALT 2026
Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streams AAAI 2025
Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation AAAI 2025
The Indoor-Training Effect: Unexpected Gains from Distribution Shifts in the Transition Function AAAI 2025
Mining In-distribution Attributes in Outliers for Out-of-distribution Detection AAAI 2025
Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data AAAI 2025
Metric-Agnostic Continual Learning for Sustainable Group Fairness AAAI 2025
Early Concept Drift Detection via Prediction Uncertainty AAAI 2025
A Layer Selection Approach to Test Time Adaptation AAAI 2025
Boosting Test Performance with Importance Sampling--a Subpopulation Perspective AAAI 2025
Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning AAAI 2025
Fully Test-time Adaptation for Tabular Data AAAI 2025
Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval AAAI 2025
Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation ACL 2025
Beyond Accuracy: Revisiting Out-of-Distribution Generalization in NLI Models ACL 2025
Beyond Clean Training Data: A Versatile and Model-Agnostic Framework for Out-of-Distribution Detection with Contaminated Training Data CVPR 2025
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection CVPR 2025
Open Set Label Shift with Test Time Out-of-Distribution Reference CVPR 2025
Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data? EMNLP 2025
Distribution Learning with Valid Outputs Beyond the Worst-Case NIPS 2024
Communication-Efficient Federated Group Distributionally Robust Optimization NIPS 2024