pre-trained model
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Pre-trainedAdversarialPerturbations
However, much less effort has been devoted to exploring the adversarial robustness of pre-trained models.
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Stabilizing Zero-Shot Prediction: A Novel Antidote to Forgetting in Continual Vision-Language Tasks Zijian Gao
Continual learning (CL) empowers pre-trained vision-language (VL) models to efficiently adapt to a sequence of downstream tasks.
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Mixture of Experts Meets Prompt-Based Continual Learning Minh Le3 An Nguyen 2 Huy Nguyen 1 Trang Nguyen
However, current AI models often fail to retain this ability.
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Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning Xu Y ang 1 Chen Liu 1 Ying Wei 2 1 City University of Hong Kong
Extensive evaluations demonstrate that AMT yields significant improvements, up to 12.92% in
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Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
Diffusion models have significantly advanced the field of generative modeling.
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CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss
The learnt models in the latter domain can then be used for a diverse set of tasks in a zero-shot way, similar to "Contrastive Language-Image
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