papers

Publications (25)

cs.CL2025

DS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design

Yanting Li, Jiyue Jiang, Zikang Wang +11

Inverse Protein Folding (IPF) is a critical subtask in the field of protein design, aiming to engineer amino acid sequences capable of folding correctly into a specified three-dime…

eess.IV2025

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Fubao Zhu, Yang Zhang, Gengmin Liang +13

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and post-capillary PH is critical for…

cs.LG2025

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Gongbo Zhang, Yanting Li, Renqian Luo +31

Function in natural systems arises from one-dimensional sequences forming three-dimensional structures with specific properties. However, current generative models suffer from crit…

eess.IV2023

Incremental Value and Interpretability of Radiomics Features of Both Lung and Epicardial Adipose Tissue for Detecting the Severity of COVID-19 Infection

Ni Yao, Yanhui Tian, Daniel Gama das Neves +9

Epicardial adipose tissue (EAT) is known for its pro-inflammatory properties and association with Coronavirus Disease 2019 (COVID-19) severity. However, current EAT segmentation me…

cs.CL2020

CLUE: A Chinese Language Understanding Evaluation Benchmark

Liang Xu, Hai Hu, Xuanwei Zhang +29

The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks. These com…

cs.CV2025

Q-CLIP: Unleashing the Power of Vision-Language Models for Video Quality Assessment through Unified Cross-Modal Adaptation

Yachun Mi, Yu Li, Yanting Li +6

Accurate and efficient Video Quality Assessment (VQA) has long been a key research challenge. Current mainstream VQA methods typically improve performance by pretraining on large-s…