2 citations · 2 across the 5 of their papers we have counts for
7 papers
GeoAlignCLIP: Enhancing Fine-Grained Vision-Language Alignment in Remote Sensing via Multi-Granular Consistency Learning
Xiao Yang, Ronghao Fu, Zhuoran Duan +3
Vision-language pretraining models have made significant progress in bridging remote sensing imagery with natural language. However, existing approaches often fail to effectively i…
GeoSolver: Scaling Test-Time Reasoning in Remote Sensing with Fine-Grained Process Supervision
Lang Sun, Ronghao Fu, Zhuoran Duan +3
While Vision-Language Models (VLMs) have significantly advanced remote sensing interpretation, enabling them to perform complex, step-by-step reasoning remains highly challenging.…
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
Riting Xia, Rucong Wang, Yulin Liu +3
Class-imbalanced graph node classification is a practical yet underexplored research problem. Although recent studies have attempted to address this issue, they typically assume cl…
A Collaborative Framework Integrating Large Language Model and Chemical Fragment Space: Mutual Inspiration for Lead Design
Hao Tuo, Yan Li, Xuanning Hu +3
Combinatorial optimization algorithm is essential in computer-aided drug design by progressively exploring chemical space to design lead compounds with high affinity to target prot…
GenShin: Guiding Rational Liposome Design by Ranking Liposomal Protein Corona through a Docking-Pose-Free GNN
Pingfei Zhu, Hongyi Liu, Xueyan Liu +2
Rational design of lipid nanoparticles (LNPs) for tissue-specific delivery critically depends on predicting the composition of the protein corona that forms on the lipid surface af…
Incomplete Graph Learning: A Comprehensive Survey
Riting Xia, Huibo Liu, Anchen Li +4
Graph learning is a prevalent field that operates on ubiquitous graph data. Effective graph learning methods can extract valuable information from graphs. However, these methods ar…
A Novel Neural-symbolic System under Statistical Relational Learning
Dongran Yu, Xueyan Liu, Shirui Pan +2
A key objective in the field of artificial intelligence is to develop cognitive models that can exhibit human-like intellectual capabilities. One promising approach to achieving th…