4 papers
ProtTeX-CC: Activating In-Context Learning in Protein LLM via Two-Stage Instruction Compression
Chuanliu Fan, Zicheng Ma, Jun Gao +5
Recent advances in protein large language models, such as ProtTeX, represent both side-chain amino acids and backbone structure as discrete token sequences of residue length. While…
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models
Zicheng Ma, Chuanliu Fan, Zhicong Wang +7
Large language models have made remarkable progress in the field of molecular science, particularly in understanding and generating functional small molecules. This success is larg…
ChatMol: A Versatile Molecule Designer Based on the Numerically Enhanced Large Language Model
Chuanliu Fan, Ziqiang Cao, Zicheng Ma +5
Goal-oriented de novo molecule design, namely generating molecules with specific property or substructure constraints, is a crucial yet challenging task in drug discovery. Existing…
Prot2Chat: Protein LLM with Early-Fusion of Text, Sequence and Structure
Zhicong Wang, Zicheng Ma, Ziqiang Cao +3
Motivation: Proteins are of great significance in living organisms. However, understanding their functions encounters numerous challenges, such as insufficient integration of multi…