Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A comprehensive survey on test-time adaptation under distribution shifts
Abstract Machine learning methods strive to acquire a robust model during the training
process that can effectively generalize to test samples, even in the presence of distribution …
process that can effectively generalize to test samples, even in the presence of distribution …
A comprehensive survey of forgetting in deep learning beyond continual learning
Forgetting refers to the loss or deterioration of previously acquired knowledge. While
existing surveys on forgetting have primarily focused on continual learning, forgetting is a …
existing surveys on forgetting have primarily focused on continual learning, forgetting is a …
Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization
This paper presents a simple yet effective approach that improves continual test-time
adaptation (TTA) in a memory-efficient manner. TTA may primarily be conducted on edge …
adaptation (TTA) in a memory-efficient manner. TTA may primarily be conducted on edge …
Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need
Class-incremental learning (CIL) aims to adapt to emerging new classes without forgetting
old ones. Traditional CIL models are trained from scratch to continually acquire knowledge …
old ones. Traditional CIL models are trained from scratch to continually acquire knowledge …