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AI agent uses LLMs for interpretable molecular structure elucidation

Researchers have developed NMRAgent, an AI system designed to interpret Nuclear Magnetic Resonance (NMR) spectra for molecular structure elucidation. This agent utilizes large language models and specialized tools to mimic human expert reasoning, planning the elucidation process, proposing structures, and verifying atom-peak consistency. NMRAgent demonstrates improved accuracy and interpretability compared to existing methods, showing practical utility in identifying novel natural products and correcting literature errors. AI

IMPACT This research could accelerate drug discovery and chemical analysis by providing more accurate and interpretable molecular structure elucidation.

RANK_REASON The cluster contains an academic paper detailing a new AI model and its performance on a scientific benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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AI agent uses LLMs for interpretable molecular structure elucidation

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zheng Fang, Chen Yang, Yusen Tan, Yunpeng Zhao, Fanjie Xu, Hongxin Xiang, Hanyu Sun, Hanyu Gao, Xiaojian Wang, Wenjie Du, Yuqiang Li, Jun Xia ·

    Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent

    arXiv:2606.29776v1 Announce Type: cross Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown molecules remains a bottleneck reliant on human expertise. While artificial intel…