activity
20222026
most citedDual-perspective Cross Contrastive Learning in Graph Transformers

1 citations · 5 across the 20 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.LG2025

FP-AbDiff: Improving Score-based Antibody Design by Capturing Nonequilibrium Dynamics through the Underlying Fokker-Planck Equation

Jiameng Chen, Yida Xiong, Kun Li +4

Computational antibody design holds immense promise for therapeutic discovery, yet existing generative models are fundamentally limited by two core challenges: (i) a lack of dynami…

cs.LG2025

Transport-Coupled Bayesian Flows for Molecular Graph Generation

Yida Xiong, Jiameng Chen, Kun Li +5

Molecular graph generation (MGG) is essentially a multi-class generative task, aimed at predicting categories of atoms and bonds under strict chemical and structural constraints. H…

cs.LG2025

Zero-Shot Learning with Subsequence Reordering Pretraining for Compound-Protein Interaction

Hongzhi Zhang, Zhonglie Liu, Kun Meng +6

Given the vastness of chemical space and the ongoing emergence of previously uncharacterized proteins, zero-shot compound-protein interaction (CPI) prediction better reflects the p…

cs.LG2025

Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding

Jiameng Chen, Xiantao Cai, Jia Wu +1

Antibody design remains a critical challenge in therapeutic and diagnostic development, particularly for complex antigens with diverse binding interfaces. Current computational met…

cs.CL2025

Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph

Yuxiang Wang, Xiao Yan, Shiyu Jin +6

Text-attributed graph (TAG) provides a text description for each graph node, and few- and zero-shot node classification on TAGs have many applications in fields such as academia an…

cs.LG2025

Knowledge-aware contrastive heterogeneous molecular graph learning

Mukun Chen, Jia Wu, Shirui Pan +4

Molecular representation learning is pivotal in predicting molecular properties and advancing drug design. Traditional methodologies, which predominantly rely on homogeneous graph…

cs.LG2025

Graph-structured Small Molecule Drug Discovery Through Deep Learning: Progress, Challenges, and Opportunities

Kun Li, Yida Xiong, Hongzhi Zhang +4

Due to their excellent drug-like and pharmacokinetic properties, small molecule drugs are widely used to treat various diseases, making them a critical component of drug discovery.…

q-bio.BM2025

Can Molecular Evolution Mechanism Enhance Molecular Representation?

Kun Li, Longtao Hu, Xiantao Cai +2

Molecular evolution is the process of simulating the natural evolution of molecules in chemical space to explore potential molecular structures and properties. The relationships be…