42 citations · 59 across the 17 of their papers we have counts for
8 papers · 1 filter
AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts
Vishal Kumar, Zeyi Liao, Jaylen Jones +1
Although large language models (LLMs) are typically aligned, they remain vulnerable to jailbreaking through either carefully crafted prompts in natural language or, interestingly,…
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang +5
Foundation model-based agents are increasingly used to automate complex tasks, enhancing efficiency and productivity. However, their access to sensitive resources and autonomous de…
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning +17
The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…
EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
Zeyi Liao, Lingbo Mo, Chejian Xu +6
Generalist web agents have demonstrated remarkable potential in autonomously completing a wide range of tasks on real websites, significantly boosting human productivity. However,…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs
Zeyi Liao, Huan Sun
As large language models (LLMs) become increasingly prevalent and integrated into autonomous systems, ensuring their safety is imperative. Despite significant strides toward safety…
AttributionBench: How Hard is Automatic Attribution Evaluation?
Yifei Li, Xiang Yue, Zeyi Liao +1
Modern generative search engines enhance the reliability of large language model (LLM) responses by providing cited evidence. However, evaluating the answer's attribution, i.e., wh…
A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents
Lingbo Mo, Zeyi Liao, Boyuan Zheng +3
Language agents powered by large language models (LLMs) have seen exploding development. Their capability of using language as a vehicle for thought and communication lends an incr…