conftrace_

distribution shift

722 papers

Explore in graph

Also known as

DS

Co-occurring keywords

domain adaptation (4595) domain generalization (1522) out-of-distribution detection (617) test-time adaptation (312) out-of-distribution generalization (408) causal inference (1630) representation learning (6206) transfer learning (5449) covariate shift (157) graph neural network (3962)

Papers

SUB: Benchmarking CBM Generalization via Synthetic Attribute Substitutions ICCV 2025
AdaO2B: Adaptive Online to Batch Conversion for Out-of-Distribution Generalization AAAI 2025
Towards Generalizable Neural Simulators: Addressing Distribution Shifts Induced by Environmental and Temporal Variations IJCAI 2025
AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks AAAI 2025
Processing and acquisition traces in visual encoders: What does CLIP know about your camera? ICCV 2025
Bridging the Gap for Test-Time Multimodal Sentiment Analysis AAAI 2025
Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation AAAI 2025
Fully Test-Time Adaptation for Feature Decrement in Tabular Data IJCAI 2025
DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale, Volunteer-Collected Biodiversity Datasets AAAI 2025
RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability AAAI 2025
Selective Uncertainty Propagation in Offline RL AAAI 2025
Towards Trustworthy Machine Learning Under Distribution Shifts AAAI 2025
Progressive Test Time Energy Adaptation for Medical Image Segmentation ICCV 2025
The Indoor-Training Effect: Unexpected Gains from Distribution Shifts in the Transition Function AAAI 2025
Fully Test-time Adaptation for Tabular Data AAAI 2025
A Unified Interpretation of Training-Time Out-of-Distribution Detection ICCV 2025
Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data? EMNLP 2025
When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs EMNLP 2025
Does Data Contamination Detection Work (Well) for LLMs? A Survey and Evaluation on Detection Assumptions NAACL 2025
Enpowering Your Pansharpening Models with Generalizability: Unified Distribution is All You Need ICCV 2025
Test-Time Visual In-Context Tuning CVPR 2025
Beyond Clean Training Data: A Versatile and Model-Agnostic Framework for Out-of-Distribution Detection with Contaminated Training Data CVPR 2025
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning AAAI 2025
OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection CVPR 2025
Phases of Uncertainty: Confidence–Calibration Dynamics in Language Model Training EMNLP 2025