NeurIPS2024
Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation
Kehan Guo, Bozhao Nan, Yujun Zhou, Taicheng Guo, Zhichun Guo, Mihir Surve, Zhenwen Liang, Nitesh V. Chawla, Olaf Wiest, Xiangliang Zhang
Abstract
Large Language Models (LLMs) have shown significant problem-solving capabili-1 ties across predictive and generative tasks in chemistry. However, their proficiency 2 in multi-step chemical reasoning remains underexplored. We introduce a new 3 challenge: molecular structure elucidation, which involves deducing a molecule’s 4 structure from various types of spectral data. Solving such a molecular puzzle, 5 akin to solving crossword puzzles, poses reasoning challenges that require inte-6