14 citations · 32 across the 24 of their papers we have counts for
9 papers · 1 filter
ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design
Yulin Zhang, He Cao, Zihao Jiang +6
Designing proteins with desired functions or properties represents a core goal in synthetic biology and drug discovery. Recent advances in protein language models (PLMs) have enabl…
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…
GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling
Tianhao Chen, Xin Xu, Zijing Liu +12
Modern Large Language Models, such as the LLaMA, Qwen and DeepSeek series, predominantly adopt the Pre-LayerNorm (Pre-LN) Transformer architecture. While being stable during pretra…
Efficient Antibody Structure Refinement Using Energy-Guided SE(3) Flow Matching
Jiying Zhang, Zijing Liu, Shengyuan Bai +3
Antibodies are proteins produced by the immune system that recognize and bind to specific antigens, and their 3D structures are crucial for understanding their binding mechanism an…
Parameter-Efficient Fine-Tuning via Circular Convolution
Aochuan Chen, Jiashun Cheng, Zijing Liu +4
Low-Rank Adaptation (LoRA) has gained popularity for fine-tuning large foundation models, leveraging low-rank matrices and to represent weight changes (i.…