2 citations · 5 across the 9 of their papers we have counts for
9 papers
Pushing Biomolecular Utility-Diversity Frontiers with Supergroup Relative Policy Optimization
Xinwu Ye, He Cao, Hao Li +5
Biomolecular generators are often adapted with reward feedback to improve task-specific utility, but pushing utility alone can concentrate generation on a narrow family of candidat…
ReactBench: A Benchmark for Topological Reasoning in MLLMs on Chemical Reaction Diagrams
Qiang Xu, Shengyuan Bai, Yu Wang +6
Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced with complex topological str…
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…
SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning
Jiying Zhang, Zijing Liu, Yu Wang +1
Molecular representation learning has shown great success in advancing AI-based drug discovery. The core of many recent works is based on the fact that the 3D geometric structure o…
SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM
Jiayi Pan, Chengcan Wang, Kaifu Zheng +3
Large language models (LLMs) have shown remarkable capabilities in various tasks. However their huge model size and the consequent demand for computational and memory resources als…