2 citations · 3 across the 9 of their papers we have counts for
9 papers
ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediation
Zesheng Wei, Mengfan Li, Wenhao Liu +3
Dispute mediation is essential for maintaining social harmony and resilience, yet developing skilled mediators is costly and time-consuming. Existing LLM-based mediation research r…
Do LLMs Understand Personality? Rethinking Persona Fidelity Evaluation through Structured Behavioral Inference
Mengfan Li, Zesheng Wei, Xuanhua Shi +1
As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an agent's behavior consistently…
From Prompt to Harness: Coderlet from Scratch
Mengfan Li
A model alone does not determine how a programming agent acts. What the model sees, how actions enter the environment, how feedback returns, and how one run affects the next all de…
Know Before Fix: QA-Driven Repository Knowledge Acquisition for Software Issue Resolution
Haotian Lin, Silin Chen, Xiaodong Gu +8
LLM-based coding agents have significantly advanced automated software issue resolution, yet they remain highly prone to factual errors caused by insufficient repository understand…
CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models
Mengfan Li, Xuanhua Shi, Yang Deng
Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demonstrate promising performance o…
EffiSkill: Agent Skill Based Automated Code Efficiency Optimization
Zimu Wang, Yuling Shi, Mengfan Li +4
Code efficiency is a fundamental aspect of software quality, yet how to harness large language models (LLMs) to optimize programs remains challenging. Prior approaches have sought…
Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions
Venkatesh Sivaraman, Eric P. Mason, Mengfan Ellen Li +4
Artificial intelligence (AI)-based decision support systems can be highly accurate yet still fail to support users or improve decisions. Existing theories of AI-assisted decision-m…
RecToM: A Benchmark for Evaluating Machine Theory of Mind in LLM-based Conversational Recommender Systems
Mengfan Li, Xuanhua Shi, Yang Deng
Large Language models are revolutionizing the conversational recommender systems through their impressive capabilities in instruction comprehension, reasoning, and human interactio…
Hyperbolic Hypergraph Neural Networks for Multi-Relational Knowledge Hypergraph Representation
Mengfan Li, Xuanhua Shi, Chenqi Qiao +2
Knowledge hypergraphs generalize knowledge graphs using hyperedges to connect multiple entities and depict complicated relations. Existing methods either transform hyperedges into…