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MinerU.Chem system achieves 93% accuracy in chemical structure recognition

By PulseAugur Editorial · [1 sources] ·

A new system called MinerU.Chem has been developed to extract chemical structures and reactions from organic chemistry documents, converting them into machine-readable data. This system, integrated into the MinerU platform, uses a core representation called CARBON to preserve visual layout and chemical semantics. In evaluations, MinerU.Chem achieved a 93.02% accuracy in recognizing molecular structures, significantly outperforming GPT 5.6 "Sol" by over 18 percentage points on the MolRecBench-Wild dataset. AI

IMPACT This system could accelerate AI for Chemistry tasks like reaction prediction and drug design by enabling better data extraction from scientific literature.

RANK_REASON The item is a research paper detailing a new system for chemical structure recognition. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MinerU.Chem system achieves 93% accuracy in chemical structure recognition

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The item is a research paper detailing a new system for chemical structure recognition. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Haote Yang, Jiang Wu, Jingchao Wang, Xingjian Wei, Lixin Ma, Linye Li, Chen Zhu, Xiaolong Wu, Yuheng Lu, Ziran Zhu, Junyuan Gao, Lingli Ge, Yuan Xu, Huijie Ao, QianQian Wu, Dechen Lin, Huaiyu Gu, Lu Chen, Shengxin Lu, ShaSha Wang, Yuanyuan Cao, Zhejia Yu… ·

    MinerU.Chem: A High-Precision System for Optical Chemical Structure and Reaction Recognition

    arXiv:2608.03525v1 Announce Type: new Abstract: In organic chemistry papers and patents, molecular structures, reaction schemes, and experimental conditions are often presented as molecular structure depictions, reaction diagrams, and complex tables or figures. Such information i…

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