42 citations · 127 across the 41 of their papers we have counts for
6 papers · 1 filter
Learning to Accumulate Knowledge with Mutual Information
Yuyang Zhao, Lizi Liao, Leyang Shen +4
Large language model (LLM) agents can improve their performance by reusing knowledge distilled from past interactions. However, curating new experiences into a knowledge bank that…
HASTE: Evolving Agent Harnesses Against Emerging Attacks Using Sparse Evidence
Xiqiao Xiong, Moxin Li, Zhixin Ma +4
Agent harnesses play a critical role in defenses by enforcing safety constraints to prevent unsafe actions. However, rapidly emerging attacks outpace manual harness adaptation, mot…
When Upstream Messages Override Correct Answers: A Controlled Study of Multi-Agent LLM Collaboration
Yaxin Gong, Gangyi Zhang, Chongming Gao +7
Multi-agent LLM systems rely on message passing among specialized agents to accomplish complex tasks. However, an upstream agent may provide useful information or an incorrect answ…
AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security
Dongrui Liu, Yu Li, Zhonghao Yang +47
Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhile, advanced frontier AI mod…
AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance
Yuyang Zhao, Wentao Shi, Fuli Feng +1
Large language model (LLM)-based agents have demonstrated remarkable capabilities in addressing complex tasks, thereby enabling more advanced information retrieval and supporting d…
Reinforced Latent Reasoning for LLM-based Recommendation
Yang Zhang, Wenxin Xu, Xiaoyan Zhao +4
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities in complex problem-solving tasks, sparking growing interest in their application to preference reas…