52 citations · 83 across the 21 of their papers we have counts for
9 papers · 1 filter
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…
-GAN by Rényi Cross Entropy
Ni Ding, Miao Qiao, Jiaxing Xu +2
This paper proposes -GAN, a generative adversarial network using Rényi measures. The value function is formulated, by Rényi cross entropy, as an expected certainty measure incur…
BrainPrompt: Multi-Level Brain Prompt Enhancement for Neurological Condition Identification
Jiaxing Xu, Kai He, Yue Tang +5
Neurological conditions, such as Alzheimer's Disease, are challenging to diagnose, particularly in the early stages where symptoms closely resemble healthy controls. Existing brain…
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…
Divergent Paths: Separating Homophilic and Heterophilic Learning for Enhanced Graph-level Representations
Han Lei, Jiaxing Xu, Xia Dong +1
Graph Convolutional Networks (GCNs) are predominantly tailored for graphs displaying homophily, where similar nodes connect, but often fail on heterophilic graphs. The strategy of…
ABXI: Invariant Interest Adaptation for Task-Guided Cross-Domain Sequential Recommendation
Qingtian Bian, Marcus Vinícius de Carvalho, Tieying Li +3
Cross-Domain Sequential Recommendation (CDSR) has recently gained attention for countering data sparsity by transferring knowledge across domains. A common approach merges domain-s…
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
Jiaxing Xu, Yongqiang Chen, Xia Dong +5
In neuroscience, identifying distinct patterns linked to neurological disorders, such as Alzheimer's and Autism, is critical for early diagnosis and effective intervention. Graph N…