4 citations · 6 across the 3 of their papers we have counts for
5 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…
From Static Structures to Ensembles: Studying and Harnessing Protein Structure Tokenization
Zijing Liu, Bin Feng, He Cao +1
Protein structure tokenization converts 3D structures into discrete or vectorized representations, enabling the integration of structural and sequence data. Despite many recent wor…
Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations
Hao Li, He Cao, Bin Feng +6
While large language models (LLMs) with Chain-of-Thought (CoT) reasoning excel in mathematics and coding, their potential for systematic reasoning in chemistry, a domain demanding…
Rethinking Text-based Protein Understanding: Retrieval or LLM?
Juntong Wu, Zijing Liu, He Cao +6
In recent years, protein-text models have gained significant attention for their potential in protein generation and understanding. Current approaches focus on integrating protein-…
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…