14 citations · 75 across the 28 of their papers we have counts for
7 papers · 1 filter
MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining
Xi Fang, Haocheng Lu, Han Lyu +3
Optical Chemical Structure Recognition (OCSR) is a fundamental component of chemical literature mining, enabling molecular database construction, reaction extraction, and AI-driven…
ProtoCycle: Reflective Tool-Augmented Planning for Text-Guided Protein Design
Yutang Ge, Guojiang Zhao, Sihang Li +7
Designing proteins that satisfy natural language functional requirements is a central goal in protein engineering. A straightforward baseline is to fine-tune generic instruction-tu…
Experimental Powder X-ray Diffraction Crystal Structure Determination with RealPXRD-Solver
Qi Li, Mingyu Guo, Rui Jiao +14
Determining crystal structures from experimental powder X-ray diffraction data remains challenging because peak overlap, preferred orientation, and impurity phases obscure atomic a…
Draft-Refine-Optimize: Self-Evolved Learning for Natural Language to MongoDB Query Generation
Mingwei Ye, Jiaxi Zhuang, Mingjun Xu +3
Natural Language to MongoDB Query Language (NL2MQL) is essential for democratizing access to modern document-centric databases. Unlike Text-to-SQL, NL2MQL faces unique challenges f…
SpecXMaster Technical Report
Yutang Ge, Yaning Cui, Hanzheng Li +15
Intelligent spectroscopy serves as a pivotal element in AI-driven closed-loop scientific discovery, functioning as the critical bridge between matter structure and artificial intel…
OmniScience: A Large-scale Multi-modal Dataset for Scientific Image Understanding
Haoyi Tao, Chaozheng Huang, Nan Wang +4
Multimodal Large Language Models demonstrate strong performance on natural image understanding, yet exhibit limited capability in interpreting scientific images, including but not…
RxnBench: A Multimodal Benchmark for Evaluating Large Language Models on Chemical Reaction Understanding from Scientific Literature
Hanzheng Li, Xi Fang, Yixuan Li +9
The integration of Multimodal Large Language Models (MLLMs) into chemistry promises to revolutionize scientific discovery, yet their ability to comprehend the dense, graphical lang…