conftrace_

distribution shift

722 papers

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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

EvoCL: Continual Learning over Evolving Domains WACV 2025
When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs EMNLP 2025
Realistic Test-Time Adaptation of Vision-Language Models CVPR 2025
ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction ICCV 2025
Automatic De-Biased Temporal-Relational Modeling for Stock Investment Recommendation IJCAI 2024
Density-Regression: Efficient and Distance-aware Deep Regressor for Uncertainty Estimation under Distribution Shifts AISTATS 2024
Supervised Algorithmic Fairness in Distribution Shifts: A Survey IJCAI 2024
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation NIPS 2024
Elijah: Eliminating Backdoors Injected in Diffusion Models via Distribution Shift AAAI 2024
Decoupled Invariant Attention Network for Multivariate Time-series Forecasting IJCAI 2024
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models NIPS 2024
Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting IJCAI 2024
Energy-based Epistemic Uncertainty for Graph Neural Networks NIPS 2024
The Inter-batch Diversity of Samples in Experience Replay for Continual Learning AAAI 2024
NanoAdapt: Mitigating Negative Transfer in Test Time Adaptation with Extremely Small Batch Sizes IJCAI 2024
Mind the Graph When Balancing Data for Fairness or Robustness NIPS 2024
Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning NIPS 2024
On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation CVPR 2024
Distributionally Robust Performative Prediction NIPS 2024
Label Alignment Regularization for Distribution Shift JMLR 2024
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations for Universal Robustness NIPS 2024
Linear Regression With Unmatched Data: A Deconvolution Perspective JMLR 2024
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts JMLR 2024
Multilingual Diversity Improves Vision-Language Representations NIPS 2024
REALM: Robust Entropy Adaptive Loss Minimization for Improved Single-Sample Test-Time Adaptation WACV 2024