Feb. 13, 2024, 5:49 a.m. | Di Zhang Wei Liu Qian Tan Jingdan Chen Hang Yan Yuliang Yan Jiatong Li Weiran Huang Xi

cs.CL updates on arXiv.org arxiv.org

Large language models (LLMs) have made impressive progress in chemistry applications, including molecular property prediction, molecular generation, experimental protocol design, etc. However, the community lacks a dialogue-based model specifically designed for chemistry. The challenge arises from the fact that most chemical data and scientific knowledge are primarily stored in structured databases, and the direct use of these structured data compromises the model's ability to maintain coherent dialogue. To tackle this issue, we develop a novel template-based instruction construction method that …

applications challenge chemistry community cs.ai cs.cl data databases design dialogue etc experimental knowledge language language model language models large language large language model large language models llms prediction progress property protocol

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