arXiv cs.CL论文
语言模型与视觉语言模型中的后门学习
arxiv.org作者：Weimin Lyu论文AI评分：70/100
该论文探讨了深度学习中自然语言处理和视觉语言模型面临的后门攻击安全威胁，并提出了分析和检测方法，同时研究了面向临床和医学影像应用的高效多模态表示学习方法。
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Abstract:Recent advances in deep learning have significantly enhanced the capabilities of Natural Language Processing (NLP) and Vision-Language Models (VLMs). However, these advancements come with increased vulnerabilities, notably through backdoor attacks that pose severe security threats. This thesis addresses two critical dimensions of Trustworthy AI and Efficient Multimodal Representation Learning: (1) security through analyzing, detecting, and designing backdoor attacks in NLP and VLMs, and (2) efficiency through advanced multimodal representation methods tailored for clinical and medical imaging applications.