most citedChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning

4 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2025

CellForge: Agentic Design of Virtual Cell Models

Xiangru Tang, Zhuoyun Yu, Jiapeng Chen +12

Virtual cell modeling aims to predict cellular responses to diverse perturbations but faces challenges from biological complexity, multimodal data heterogeneity, and the need for i…

cs.LG2025

STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics

Joao F. Rocha, Ke Xu, Xingzhi Sun +6

The advent of single-cell technology has significantly improved our understanding of cellular states and subpopulations in various tissues under normal and diseased conditions by e…

cs.CL2025

Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards

Jaehoon Yun, Jiwoong Sohn, Jungwoo Park +9

Large language models have shown promise in clinical decision making, but current approaches struggle to localize and correct errors at specific steps of the reasoning process. Thi…

cs.CL20254 cited

ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning

Xiangru Tang, Tianyu Hu, Muyang Ye +9

Chemical reasoning usually involves complex, multi-step processes that demand precise calculations, where even minor errors can lead to cascading failures. Furthermore, large langu…

cs.CL20242 cited

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain

Haochen Zhao, Xiangru Tang, Ziran Yang +8

The advancement and extensive application of large language models (LLMs) have been remarkable, including their use in scientific research assistance. However, these models often g…