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Test-time Adaptation

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Showing 276–300 of 484 papers

TitleStatusHype
Keeping Medical AI Healthy: A Review of Detection and Correction Methods for System Degradation—0
Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation—0
Label Shift Adapter for Test-Time Adaptation under Covariate and Label Shifts—0
Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models—0
Layerwise Early Stopping for Test Time Adaptation—0
LeanTTA: A Backpropagation-Free and Stateless Approach to Quantized Test-Time Adaptation on Edge Devices—0
Learning Domain-Invariant Features for Out-of-Context News Detection—0
Learning Instance-Specific Adaptation for Cross-Domain Segmentation—0
Learning Less Generalizable Patterns with an Asymmetrically Trained Double Classifier for Better Test-Time Adaptation—0
Learning to Adapt to Online Streams with Distribution Shifts—0
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation—0
Low Saturation Confidence Distribution-based Test-Time Adaptation for Cross-Domain Remote Sensing Image Classification—0
MADCAT: Combating Malware Detection Under Concept Drift with Test-Time Adaptation—0
Maintaining Consistent Inter-Class Topology in Continual Test-Time Adaptation—0
Maintain Plasticity in Long-timescale Continual Test-time Adaptation—0
ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation—0
MedBN: Robust Test-Time Adaptation against Malicious Test Samples—0
Toward generalizable learning of all (linear) first-order methods via memory augmented Transformers—0
Meta-Auxiliary Learning for Adaptive Human Pose Prediction—0
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions—0
SMILE: Speech Meta In-Context Learning for Low-Resource Language Automatic Speech Recognition—0
MeTTA: Single-View to 3D Textured Mesh Reconstruction with Test-Time Adaptation—0
MINGLE: Mixtures of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Merging—0
MITA: Bridging the Gap between Model and Data for Test-time Adaptation—0
Mitigating Cache Noise in Test-Time Adaptation for Large Vision-Language Models—0
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