1 citations · 5 across the 13 of their papers we have counts for
5 papers · 1 filter
Any-Depth Alignment: Unlocking Innate Safety Alignment of LLMs to Any-Depth
Jiawei Zhang, Andrew Estornell, David D. Baek +2
Large Language Models (LLMs) exhibit strong but shallow alignment: they directly refuse harmful queries when a refusal is expected at the very start of an assistant turn, yet this…
ARMs: Adaptive Red-Teaming Agent against Multimodal Models with Plug-and-Play Attacks
Zhaorun Chen, Xun Liu, Mintong Kang +4
As vision-language models (VLMs) gain prominence, their multimodal interfaces also introduce new safety vulnerabilities, making the safety evaluation challenging and critical. Exis…
Poly-Guard: Massive Multi-Domain Safety Policy-Grounded Guardrail Dataset
Mintong Kang, Zhaorun Chen, Chejian Xu +6
As LLMs become widespread across diverse applications, concerns about the security and safety of LLM interactions have intensified. Numerous guardrail models and benchmarks have be…
UDora: A Unified Red Teaming Framework against LLM Agents by Dynamically Hijacking Their Own Reasoning
Jiawei Zhang, Shuang Yang, Bo Li
Large Language Model (LLM) agents equipped with external tools have become increasingly powerful for complex tasks such as web shopping, automated email replies, and financial trad…
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Jiawei Zhang, Xuan Yang, Taiqi Wang +3
Traditional autonomous driving systems often struggle to connect high-level reasoning with low-level control, leading to suboptimal and sometimes unsafe behaviors. Recent advances…