most citedAgentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis

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cs.LG2026★ 2 cited

Agentic reinforcement learning empowers next-generation chemical language models for molecular design and synthesis

Hao Li, He Cao, Shenyao Peng +7

Language models are revolutionizing the biochemistry domain, assisting scientists in drug design and chemical synthesis with high efficiency. Yet current approaches struggle betwee…