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20242026
most citedDiffusion Language Models Are Versatile Protein Learners

18 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Towards A Generative Protein Evolution Machine with DPLM-Evo

Xinyou Wang, Liang Hong, Jiasheng Ye +4

Proteins are shaped by gradual evolution under biophysical and functional constraints. Protein language models learn rich evolutionary constraints from large-scale sequences, and d…

cs.LG2025

Elucidating the Design Space of Multimodal Protein Language Models

Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang +5

Multimodal protein language models (PLMs) integrate sequence and token-based structural information, serving as a powerful foundation for protein modeling, generation, and design.…

cs.LG2024★ 7 cited

DPLM-2: A Multimodal Diffusion Protein Language Model

Xinyou Wang, Zaixiang Zheng, Fei Ye +3

Proteins are essential macromolecules defined by their amino acid sequences, which determine their three-dimensional structures and, consequently, their functions in all living org…

q-bio.QM2024★ 3 cited

ProteinBench: A Holistic Evaluation of Protein Foundation Models

Fei Ye, Zaixiang Zheng, Dongyu Xue +7

Recent years have witnessed a surge in the development of protein foundation models, significantly improving performance in protein prediction and generative tasks ranging from 3D…

cs.LG2024★ 18 cited

Diffusion Language Models Are Versatile Protein Learners

Xinyou Wang, Zaixiang Zheng, Fei Ye +3

This paper introduces diffusion protein language model (DPLM), a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequen…