This academic article delves into the security risks of unlabeled data in model adaptation, focusing on potential backdoor attacks. The authors provide two backdoor triggers and two poisoning strategies, achieving…
Continue readingThis research paper delves into the theoretical aspects of Low-Rank Adaptation (LoRA), a prevalent technique for fine-tuning pre-trained models like large language models and diffusion models. Despite its practical success,…
Continue readingThis research introduces a new framework named PromptSRC, aiming to improve the way prompts are used to fine-tune foundational models like CLIP for various tasks. The new approach aims to…
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