7 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
CheMatAgent: Enhancing LLMs for Chemistry and Materials Science through Tree-Search Based Tool Learning
Mengsong Wu, YaFei Wang, Yidong Ming +7
Large language models (LLMs) have recently demonstrated promising capabilities in chemistry tasks while still facing challenges due to outdated pretraining knowledge and the diffic…
cs.CL2025
SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition
Mengsong Wu, Di Zhang, Yuqiang Li +2
While Large Language Models (LLMs) have achieved remarkable success in a wide range of applications, their performance often degrades in complex reasoning tasks. In this work, we i…
cs.AI2024★ 7 cited
Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
Di Zhang, Xiaoshui Huang, Dongzhan Zhou +2
This paper introduces the MCT Self-Refine (MCTSr) algorithm, an innovative integration of Large Language Models (LLMs) with Monte Carlo Tree Search (MCTS), designed to enhance perf…