collaborators

6 papers

cs.CV2026

DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

Ziyang Gao, Zhizhuo Jiang, Jingjing Chang +5

Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Existing methods mainly follow jo…

cs.CL2026

MAP: A Meta-Cognitive Autonomous Intelligent Agents Framework for Complex Persuasion

Dingyi Zhang, Ziqing Zhuang, Linhai Zhang +2

Persuasive dialogue generation plays a vital role in decision-making, negotiation, counseling, and behavior change, yet it remains a challenging problem. In complex persuasion wher…

cs.LG2025

GastroDL-Fusion: A Dual-Modal Deep Learning Framework Integrating Protein-Ligand Complexes and Gene Sequences for Gastrointestinal Disease Drug Discovery

Ziyang Gao, Annie Cheung, Yihao Ou

Accurate prediction of protein-ligand binding affinity plays a pivotal role in accelerating the discovery of novel drugs and vaccines, particularly for gastrointestinal (GI) diseas…

stat.ME2025

Cross-Lingual Sponsored Search via Dual-Encoder and Graph Neural Networks for Context-Aware Query Translation in Advertising Platforms

Ziyang Gao, Yuanliang Qu, Yi Han

Cross-lingual sponsored search is crucial for global advertising platforms, where users from different language backgrounds interact with multilingual ads. Traditional machine tran…

cs.CL2025

Explainable Depression Detection in Clinical Interviews with Personalized Retrieval-Augmented Generation

Linhai Zhang, Ziyang Gao, Deyu Zhou +1

Depression is a widespread mental health disorder, and clinical interviews are the gold standard for assessment. However, their reliance on scarce professionals highlights the need…

eess.IV2025

A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical field

Ziyang Gao, Yong Tian, Shih-Chi Lin +1

In the medical field, accurate diagnosis of lung cancer is crucial for treatment. Traditional manual analysis methods have significant limitations in terms of accuracy and efficien…