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cs.CL2024★ 1 cited
Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation
Shuai Zhao, Xiaobao Wu, Cong-Duy Nguyen +4
Parameter-efficient fine-tuning (PEFT) can bridge the gap between large language models (LLMs) and downstream tasks. However, PEFT has been proven vulnerable to malicious attacks.…
cs.CR2024★ 2 cited
A Survey of Recent Backdoor Attacks and Defenses in Large Language Models
Shuai Zhao, Meihuizi Jia, Zhongliang Guo +7
Large Language Models (LLMs), which bridge the gap between human language understanding and complex problem-solving, achieve state-of-the-art performance on several NLP tasks, part…
cs.CL2024
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
Xiaobao Wu, Fengjun Pan, Thong Nguyen +4
Hierarchical topic modeling aims to discover latent topics from a corpus and organize them into a hierarchy to understand documents with desirable semantic granularity. However, ex…