34 citations · 34 across the 6 of their papers we have counts for
7 papers
MASTraceBench: Diagnosing Collaboration Gains through Proposal Trajectories in LLM-Based Multi-Agent Systems
Yapeng Li, Songze Li, Shuang Yu +4
LLM-based multi-agent systems (MAS) have shown promise in complex problem solving. As MAS methods diversify, systematic evaluation becomes increasingly challenging. However, existi…
A Comprehensive Evaluation of LLM Reasoning: From Single-Model to Multi-Agent Paradigms
Yapeng Li, Jiakuo Yu, Zhixin Liu +4
Large Language Models (LLMs) are increasingly deployed as reasoning systems, where reasoning paradigms - such as Chain-of-Thought (CoT) and multi-agent systems (MAS) - play a criti…
ClinDEF: A Dynamic Evaluation Framework for Large Language Models in Clinical Reasoning
Yuqi Tang, Jing Yu, Zichang Su +7
Clinical diagnosis begins with doctor-patient interaction, during which physicians iteratively gather information, determine examination and refine differential diagnosis through p…
SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
Keyan Ding, Jing Yu, Junjie Huang +3
Scientific research increasingly relies on specialized computational tools, yet effectively utilizing these tools demands substantial domain expertise. While Large Language Models…
OneEval: Benchmarking LLM Knowledge-intensive Reasoning over Diverse Knowledge Bases
Yongrui Chen, Zhiqiang Liu, Jing Yu +21
Large Language Models (LLMs) have demonstrated substantial progress on reasoning tasks involving unstructured text, yet their capabilities significantly deteriorate when reasoning…
SciCUEval: A Comprehensive Dataset for Evaluating Scientific Context Understanding in Large Language Models
Jing Yu, Yuqi Tang, Kehua Feng +8
Large Language Models (LLMs) have shown impressive capabilities in contextual understanding and reasoning. However, evaluating their performance across diverse scientific domains r…
Scientific Large Language Models: A Survey on Biological & Chemical Domains
Qiang Zhang, Keyang Ding, Tianwen Lyv +22
Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelli…