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20242026
most citedChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System

1 citations · 1 across the 10 of their papers we have counts for

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cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

cs.LG2026

Equivariant Evidential Deep Learning for Interatomic Potentials

Zhongyao Wang, Taoyong Cui, Jiawen Zou +5

Uncertainty quantification (UQ) is critical for assessing the reliability of machine learning interatomic potentials (MLIPs) in molecular dynamics (MD) simulations, identifying ext…

cs.LG20251 cited

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System

Dong Han, Zhehong Ai, Pengxiang Cai +16

Bayesian optimization (BO) is a powerful tool for scientific discovery in chemistry, yet its efficiency is often hampered by the sparse experimental data and vast search space. Her…

cs.LG2025

ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area

Junxian Li, Di Zhang, Xunzhi Wang +16

Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the…

cs.LG2025

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Weida Wang, Dongchen Huang, Jiatong Li +32

We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than…