14 citations · 31 across the 22 of their papers we have counts for
9 papers · 1 filter
Stop Reducing Responsibility in LLM-Powered Multi-Agent Systems to Local Alignment
Jinwei Hu, Yi Dong, Shuang Ao +6
LLM-powered Multi-Agent Systems (LLM-MAS) unlock new potentials in distributed reasoning, collaboration, and task generalization but also introduce additional risks due to unguaran…
Tapas Are Free! Training-Free Adaptation of Programmatic Agents via LLM-Guided Program Synthesis in Dynamic Environments
Jinwei Hu, Yi Dong, Youcheng Sun +1
Autonomous agents in safety-critical applications must continuously adapt to dynamic conditions without compromising performance and reliability. This work introduces TAPA (Trainin…
Enhancing Robustness of LLM-Driven Multi-Agent Systems through Randomized Smoothing
Jinwei Hu, Yi Dong, Zhengtao Ding +1
This paper presents a defense framework for enhancing the safety of large language model (LLM) empowered multi-agent systems (MAS) in safety-critical domains such as aerospace. We…
Hierarchical Testing with Rabbit Optimization for Industrial Cyber-Physical Systems
Jinwei Hu, Zezhi Tang, Xin Jin +3
This paper presents HERO (Hierarchical Testing with Rabbit Optimization), a novel black-box adversarial testing framework for evaluating the robustness of deep learning-based Progn…
Safe Pruning LoRA: Robust Distance-Guided Pruning for Safety Alignment in Adaptation of LLMs
Shuang Ao, Yi Dong, Jinwei Hu +1
Fine-tuning Large Language Models (LLMs) with Low-Rank Adaptation (LoRA) enhances adaptability while reducing computational costs. However, fine-tuning can compromise safety alignm…
TAIJI: Textual Anchoring for Immunizing Jailbreak Images in Vision Language Models
Xiangyu Yin, Yi Qi, Jinwei Hu +5
Vision Language Models (VLMs) have demonstrated impressive inference capabilities, but remain vulnerable to jailbreak attacks that can induce harmful or unethical responses. Existi…
CeTAD: Towards Certified Toxicity-Aware Distance in Vision Language Models
Xiangyu Yin, Jiaxu Liu, Zhen Chen +4
Recent advances in large vision-language models (VLMs) have demonstrated remarkable success across a wide range of visual understanding tasks. However, the robustness of these mode…
Position: Towards a Responsible LLM-empowered Multi-Agent Systems
Jinwei Hu, Yi Dong, Shuang Ao +6
The rise of Agent AI and Large Language Model-powered Multi-Agent Systems (LLM-MAS) has underscored the need for responsible and dependable system operation. Tools like LangChain a…
FALCON: Fine-grained Activation Manipulation by Contrastive Orthogonal Unalignment for Large Language Model
Jinwei Hu, Zhenglin Huang, Xiangyu Yin +4
Large language models have been widely applied, but can inadvertently encode sensitive or harmful information, raising significant safety concerns. Machine unlearning has emerged t…