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Recent works on parameter-efficient transfer learning (PETL) show the potential to adapt a pre-trained Vision Transformer to downstream recognition tasks with only a few learnable parameters.
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2024
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2024
Closest in time.
Li, X., Lian, D., Lu, Z., Bai, J., Chen, Z., Wang, X.: Graphadapter: Tuning vision-language models with dual knowledge graph. Advances in Neural Information Processing Systems 36
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Lu, Z., Bai, J., Li, X., Xiao, Z., Wang, X.: Beyond sole strength: Customized ensembles for generalized vision-language models. In: Forty-first International Conference on Machine Learning (2024)
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Yang, S., Bai, J., Gao, K., Yang, Y., Li, Y., Xia, S.T.: Not all prompts are secure: A switchable backdoor attack against pre-trained vision transfomers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 24431–24441 (2024)
2024
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