2 citations · 2 across the 4 of their papers we have counts for
5 papers
P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs
Shuai Zhao, Xinyi Wu, Shiqian Zhao +4
During fine-tuning, large language models (LLMs) are increasingly vulnerable to data-poisoning backdoor attacks, which compromise their reliability and trustworthiness. However, ex…
Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity
Shuai Zhao, Yulin Zhang, Luwei Xiao +7
Despite the remarkable progress of large language models (LLMs) across various domains, their capacity to predict retinopathy of prematurity (ROP) risk remains largely unexplored.…
HarmReduction: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs
Kaixuan Wang, Chenxin Diao, Jason T. Jacques +2
Millions of individuals' well-being are challenged by the harms of substance use. Harm reduction as a public health strategy provides non-judgemental, evidence-based information in…
Breaking PEFT Limitations: Leveraging Weak-to-Strong Knowledge Transfer for Backdoor Attacks in LLMs
Shuai Zhao, Leilei Gan, Zhongliang Guo +5
Despite being widely applied due to their exceptional capabilities, Large Language Models (LLMs) have been proven to be vulnerable to backdoor attacks. These attacks introduce targ…
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…