6 citations · 15 across the 5 of their papers we have counts for
Showing 2023Show all
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cs.CL2023★ 5 cited
Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information
Zhengmian Hu, Gang Wu, Saayan Mitra +4
In recent years, Large Language Models (LLM) have emerged as pivotal tools in various applications. However, these models are susceptible to adversarial prompt attacks, where attac…
cs.CR2023★ 6 cited
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models
Sicheng Zhu, Ruiyi Zhang, Bang An +6
Safety alignment of Large Language Models (LLMs) can be compromised with manual jailbreak attacks and (automatic) adversarial attacks. Recent studies suggest that defending against…