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07/31/2023
Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy
Current state-of-the-art results in computer vision depend in part on fi...
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02/23/2023
Detachedly Learn a Classifier for Class-Incremental Learning
In continual learning, model needs to continually learn a feature extrac...
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12/06/2022
FacT: Factor-Tuning for Lightweight Adaptation on Vision Transformer
Recent work has explored the potential to adapt a pre-trained vision tra...
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07/14/2022
Convolutional Bypasses Are Better Vision Transformer Adapters
The pretrain-then-finetune paradigm has been widely adopted in computer ...
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05/19/2022
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework
Continual learning requires the model to maintain the learned knowledge ...
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04/22/2022
