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In this work, we present our vision for building an AI-powered chemical brain, which frames chemical intelligence around four core capabilities: information extraction, semantic parsing, knowledge-based QA, and reasoning & planning. To initiate this effort, we introduce our first generation of large language models for chemistry: KALE-LM-Chem and KALE-LM-Chem-1.5, which have achieved outstanding performance in tasks related to the field of chemistry. We hope that our work serves as a strong starting point, helping to realize more intelligent AI. Our models are now open-source.

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KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry

  • 会议论文

  • 发表日期：

    2026年

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  • Weichen Dai,
  • Yezeng Chen,
  • Zijie Dai,
  • Yubo Liu,
  • Zhijie Huang,
  • Yixuan Pan,
  • Baiyang Song,
  • Chengli Zhong,
  • Xinhe Li,
  • Zeyu Wang,
  • Zhuoying Feng,
  • Yi Zhou

摘要

In this work, we present our vision for building an AI-powered chemical brain, which frames chemical intelligence around four core capabilities: information extraction, semantic parsing, knowledge-based QA, and reasoning & planning. To initiate this effort, we introduce our first generation of large language models for chemistry: KALE-LM-Chem and KALE-LM-Chem-1.5, which have achieved outstanding performance in tasks related to the field of chemistry. We hope that our work serves as a strong starting point, helping to realize more intelligent AI. Our models are now open-source.