2 citations · 3 across the 3 of their papers we have counts for
5 papers
Mozi: Governed Autonomy for Drug Discovery LLM Agents
He Cao, Siyu Liu, Fan Zhang +7
Tool-augmented large language model (LLM) agents promise to unify scientific reasoning with computation, yet their deployment in high-stakes domains like drug discovery is bottlene…
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…
BioMD: All-atom Generative Model for Biomolecular Dynamics Simulation
Bin Feng, Jiying Zhang, Xinni Zhang +2
Molecular dynamics (MD) simulations are essential tools in computational chemistry and drug discovery, offering crucial insights into dynamic molecular behavior. However, their uti…
A Novel 4-D Dataset Paradigm for Studying Complete Ligand-Protein Dissociation Dynamics
Maodong Li, Jiying Zhang, Zhe Wang +7
The kinetics and dynamics of drug-protein binding and dissociation are crucial to understanding drug absorption and metabolism. Despite advances in artificial intelligence (AI) too…
Dynamic Guided and Domain Applicable Safeguards for Enhanced Security in Large Language Models
Weidi Luo, He Cao, Zijing Liu +5
With the extensive deployment of Large Language Models (LLMs), ensuring their safety has become increasingly critical. However, existing defense methods often struggle with two key…