{"total":24,"rows":[{"id":"2303.15361","title":"A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts","created":"2023-03-27","cited_by_count":359,"area":null},{"id":"2310.08598","title":"Domain Generalization for Medical Image Analysis: A Review","created":"2023-10-05","cited_by_count":48,"area":null},{"id":"2310.20199","title":"In Search of Lost Online Test-time Adaptation: A Survey","created":"2023-10-31","cited_by_count":44,"area":null},{"id":"2305.06024","title":"A Survey on the Robustness of Computer Vision Models against Common Corruptions","created":"2023-05-10","cited_by_count":21,"area":null},{"id":"2403.10052","title":"T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory","created":"2024-03-15","cited_by_count":20,"area":null},{"id":"2410.15674","title":"TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight","created":"2024-10-21","cited_by_count":12,"area":null},{"id":"2402.05035","title":"A Survey on Domain Generalization for Medical Image Analysis","created":"2024-02-07","cited_by_count":9,"area":null},{"id":"2505.14511","title":"ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains","created":"2025-05-20","cited_by_count":9,"area":null},{"id":"2401.08328","title":"Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation","created":"2024-01-16","cited_by_count":7,"area":null},{"id":"2406.14878","title":"MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection","created":"2024-06-21","cited_by_count":7,"area":null},{"id":"2310.05341","title":"From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?","created":"2023-10-09","cited_by_count":5,"area":null},{"id":"2410.14729","title":"Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation","created":"2024-10-16","cited_by_count":4,"area":null},{"id":"2501.09163","title":"Towards Understanding Extrapolation: a Causal Lens","created":"2025-01-15","cited_by_count":4,"area":null},{"id":"2404.13571","title":"Test-Time Training on Graphs with Large Language Models (LLMs)","created":"2024-04-21","cited_by_count":3,"area":null},{"id":"2409.12587","title":"Test-Time Augmentation Meets Variational Bayes","created":"2024-09-19","cited_by_count":3,"area":null},{"id":"2506.23104","title":"DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation","created":"2025-06-29","cited_by_count":3,"area":null},{"id":"2604.10950","title":"Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation","created":"2026-04-13","cited_by_count":3,"area":null},{"id":"2310.20327","title":"Improving Entropy-Based Test-Time Adaptation from a Clustering View","created":"2023-10-31","cited_by_count":2,"area":null},{"id":"2506.02453","title":"PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation","created":"2025-06-03","cited_by_count":2,"area":null},{"id":"2410.01083","title":"Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-Time","created":"2024-10-01","cited_by_count":1,"area":null},{"id":"2401.14587","title":"CNG-SFDA:Clean-and-Noisy Region Guided Online-Offline Source-Free Domain Adaptation","created":"2024-01-26","cited_by_count":0,"area":null},{"id":"2507.17001","title":"Should Bias be Eliminated? A General Framework to Use Bias for OOD Generalization","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2510.07762","title":"From Noisy to Native: LLM-driven Graph Restoration for Test-Time Graph Domain Adaptation","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2606.22351","title":"Reliability-Guided Adaptive Ensembling for Robust Test-Time Adaptation","created":"2026-06-21","cited_by_count":0,"area":null}],"next_cursor":null}