activity
20212026
most citedINSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback

4 citations · 14 across the 10 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Joint Discrete and SE(3) Diffusion for Protein Interface Design

Zhenqiao Song, Jianwen Xie, Lei Li

The design of high-affinity, target-specific protein binders is central to the development of modern therapeutics. However, existing protein-generation methods remain limited in th…

cs.LG2025

PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design

Zhenqiao Song, Tiaoxiao Li, Lei Li +1

Designing protein-binding proteins with high affinity is critical in biomedical research and biotechnology. Despite recent advancements targeting specific proteins, the ability to…

cs.LG2025★ 1 cited

InstructPro: Natural Language Guided Ligand-Binding Protein Design

Zhenqiao Song, Ramith Hettiarachchi, Chuan Li +2

The de novo design of ligand-binding proteins with tailored functions is essential for advancing biotechnology and molecular medicine, yet existing AI approaches are limited by sca…

q-bio.BM2024★ 4 cited

SurfPro: Functional Protein Design Based on Continuous Surface

Zhenqiao Song, Tinglin Huang, Lei Li +1

How can we design proteins with desired functions? We are motivated by a chemical intuition that both geometric structure and biochemical properties are critical to a protein's fun…

cs.LG2024★ 2 cited

Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates

Zhenqiao Song, Yunlong Zhao, Wenxian Shi +3

Enzymes are genetically encoded biocatalysts capable of accelerating chemical reactions. How can we automatically design functional enzymes? In this paper, we propose EnzyGen, an a…

cs.CL2024★ 1 cited

Hire a Linguist!: Learning Endangered Languages with In-Context Linguistic Descriptions

Kexun Zhang, Yee Man Choi, Zhenqiao Song +3

How can large language models (LLMs) process and translate endangered languages? Many languages lack a large corpus to train a decent LLM; therefore existing LLMs rarely perform we…

cs.LG2023★ 1 cited

Joint Design of Protein Sequence and Structure based on Motifs

Zhenqiao Song, Yunlong Zhao, Yufei Song +3

Designing novel proteins with desired functions is crucial in biology and chemistry. However, most existing work focus on protein sequence design, leaving protein sequence and stru…

cs.LG2023

Functional Geometry Guided Protein Sequence and Backbone Structure Co-Design

Zhenqiao Song, Yunlong Zhao, Wenxian Shi +2

Proteins are macromolecules responsible for essential functions in almost all living organisms. Designing reasonable proteins with desired functions is crucial. A protein's sequenc…

cs.CL2023★ 4 cited

INSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback

Wenda Xu, Danqing Wang, Liangming Pan +4

Automatically evaluating the quality of language generation is critical. Although recent learned metrics show high correlation with human judgement, these metrics can not explain t…

q-bio.BM2023★ 1 cited

Importance Weighted Expectation-Maximization for Protein Sequence Design

Zhenqiao Song, Lei Li

Designing protein sequences with desired biological function is crucial in biology and chemistry. Recent machine learning methods use a surrogate sequence-function model to replace…

cs.CL2021

MTG: A Benchmark Suite for Multilingual Text Generation

Yiran Chen, Zhenqiao Song, Xianze Wu +5

We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation. It is the first-proposed multilingual multiway text generation dataset with the la…