4 citations · 6 across the 2 of their papers we have counts for
4 papers
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…
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension
Hao Li, Liuzhenghao Lv, He Cao +6
Large language models are increasingly used in scientific domains, especially for molecular understanding and analysis. However, existing models are affected by hallucination issue…
Navigating Chemical-Linguistic Sharing Space with Heterogeneous Molecular Encoding
Liuzhenghao Lv, Hao Li, Yu Wang +5
Chemical language models (CLMs) are prominent for their effectiveness in exploring chemical space and enabling molecular engineering. However, while exploring chemical-linguistic s…
Multi-granularity Score-based Generative Framework Enables Efficient Inverse Design of Complex Organics
Zijun Chen, Yu Wang, Liuzhenghao Lv +4
Efficiently retrieving an enormous chemical library to design targeted molecules is crucial for accelerating drug discovery, organic chemistry, and optoelectronic materials. Despit…