Mao Su — accepted AI-conference papers

2026

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

Weida Wang, Dongchen Huang, Jiatong LI, Tengchao Yang, Ziyang Zheng, Chuyi Peng +30

ICLR 2026poster

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 520 graduate-level meticulously curated questions covering both representative subfields and foundational theoretical f…

Cited by 0 Source ↗code ↗Scholar ↗

2025

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

Junxian Li, Di Zhang, Xunzhi Wang, Zeying Hao, Jingdi Lei, Qian Tan +13

AAAI 2025technical

Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the processing of visual information, which cannot be successfully handled by existing chemical LLMs. This brings a growing…

Cited by 9 Source ↗PDF ↗code ↗Scholar ↗