10 papers
Let ViT Speak: Generative Language-Image Pre-training
Yan Fang, Mengcheng Lan, Zilong Huang +7
In this paper, we present \textbf{Gen}erative \textbf{L}anguage-\textbf{I}mage \textbf{P}re-training (GenLIP), a minimalist generative pretraining framework for Vision Transformers…
Directed Homophily-Aware Graph Neural Network
Aihu Zhang, Jiaxing Xu, Mengcheng Lan +2
Graph Neural Networks (GNNs) have achieved significant success in various learning tasks on graph-structured data. Nevertheless, most GNNs struggle to generalize to heterophilic ne…
Multi-Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion
Jiaxing Xu, Mengcheng Lan, Xia Dong +4
In the realm of neuroscience, identifying distinctive patterns associated with neurological disorders via brain networks is crucial. Resting-state functional magnetic resonance ima…
Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration
Yue Zhou, Litong Feng, Mengcheng Lan +5
Mathematical reasoning is critical for tasks such as precise distance and area computations, trajectory estimations, and spatial analysis in unmanned aerial vehicle (UAV) based rem…
Text4Seg++: Advancing Image Segmentation via Generative Language Modeling
Mengcheng Lan, Chaofeng Chen, Jiaxing Xu +6
Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks. However, effectively integrating image segmentation into these models remains…
NOCL: Node-Oriented Conceptualization LLM for Graph Tasks without Message Passing
Wei Li, Mengcheng Lan, Jiaxing Xu +1
Graphs are essential for modeling complex interactions across domains such as social networks, biology, and recommendation systems. Traditional Graph Neural Networks, particularly…