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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…
cs.LG2024★ 4 cited
TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation
Lin Zongying, Li Hao, Lv Liuzhenghao +5
Designing protein sequences with specific biological functions and structural stability is crucial in biology and chemistry. Generative models already demonstrated their capabiliti…