6 citations · 14 across the 9 of their papers we have counts for
9 papers
DLawBench: Evaluating LLMs Through Multi-Turn Legal Consultation
Li Zhang, Yuzhen Shi, Yiran Hu +15
Lawyer-client consultation is a critical starting point for legal services. Effective legal assistance hinges on eliciting sufficient and truthful information from clients in order…
TCP-MCP: Landscape-Guided Co-Evolution of Prompts and Communication Topologies for Multi-Agent Systems
Yi Ding, Zijie Xuan, Haowei Zhou +6
Effective multi-agent systems cannot be designed by selecting prompts or communication graphs in isolation. Agent behavior depends on the information an agent receives, while the u…
The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models
Zheng Wang, Kaixuan Zhang, Wanfang Chen +2
Sequential editing of structured knowledge in large language models allows targeted factual updates without retraining, yet existing methods often rely on complex regularization or…
PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice
Yuzhen Shi, Huanghai Liu, Yiran Hu +27
As large language models (LLMs) are increasingly applied to legal domain-specific tasks, evaluating their ability to perform legal work in real-world settings has become essential.…
LLM-based Agents Suffer from Hallucinations: A Survey of Taxonomy, Methods, and Directions
Xixun Lin, Yucheng Ning, Jingwen Zhang +21
Driven by the rapid advancements of Large Language Models (LLMs), LLM-based agents have emerged as powerful intelligent systems capable of human-like cognition, reasoning, and inte…
Large Language Models for Planning: A Comprehensive and Systematic Survey
Pengfei Cao, Tianyi Men, Wencan Liu +7
Planning represents a fundamental capability of intelligent agents, requiring comprehensive environmental understanding, rigorous logical reasoning, and effective sequential decisi…
How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs
Yi Zeng, Hongpeng Lin, Jingwen Zhang +3
Most traditional AI safety research has approached AI models as machines and centered on algorithm-focused attacks developed by security experts. As large language models (LLMs) be…
Social Influence Dialogue Systems: A Survey of Datasets and Models For Social Influence Tasks
Kushal Chawla, Weiyan Shi, Jingwen Zhang +3
Dialogue systems capable of social influence such as persuasion, negotiation, and therapy, are essential for extending the use of technology to numerous realistic scenarios. Howeve…
Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot's Self-Disclosure in Conversational Recommendations
Kai-Hui Liang, Weiyan Shi, Yoojung Oh +3
Using chatbots to deliver recommendations is increasingly popular. The design of recommendation chatbots has primarily been taking an information-centric approach by focusing on th…