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# Continual Learning with Vision Transformers
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> Update: Our paper wins the best runnerup award at the [CLVision workshop](https://sites.google.com/view/clvision2022/call-for-papers/accepted-papers).
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This repo hosts the official implementation of our CVPR 2022 workshop paper [Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization](https://openaccess.thecvf.com/content/CVPR2022W/CLVision/html/Pelosin_Towards_Exemplar-Free_Continual_Learning_in_Vision_Transformers_An_Account_of_CVPRW_2022_paper.html).
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TLDR; We introduce attentional and functional variants for asymmetric and symmetric Pooled Attention Distillation (PAD) losses in Vision Transformers:

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