52 citations · 83 across the 21 of their papers we have counts for
22 papers
CoRCi: Cross-Reconstruction of Coherent Interests Modeling in Cross-Domain Sequential Recommendation
Qingtian Bian, Tieying Li, Marcus de Carvalho +3
Cross-Domain Sequential Recommendation (CDSR) aims to alleviate data sparsity by transferring dynamic user interests across related domains. A key challenge lies in effectively bri…
Return of Frustratingly Easy Unsupervised Video Domain Adaptation
Pengfei Wei, Yiqun Sun, Zhiqiang Xu +2
Unsupervised video domain adaptation (UVDA) is a practical but under-explored problem. In this paper, we propose a frustratingly easy UVDA method, called MetaTrans. Specifically, M…
Toward a Multi-View Brain Network Foundation Model: Cross-View Consistency Learning Across Arbitrary Atlases
Jiaxing Xu, Jingying Ma, Xin Lin +7
Brain network analysis provides an interpretable framework for characterizing brain organization and has been widely used for neurological disorder identification. Recent advances…
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…
GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding
Yue Zhou, Mengcheng Lan, Xiang Li +6
Remote sensing (RS) visual grounding aims to use natural language expression to locate specific objects (in the form of the bounding box or segmentation mask) in RS images, enhanci…
Text4Seg: Reimagining Image Segmentation as Text Generation
Mengcheng Lan, Chaofeng Chen, Yue Zhou +5
Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks; however, effectively integrating image segmentation into these models remains…
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…
Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
Jiaxing Xu, Kai He, Mengcheng Lan +5
Understanding neurological disorder is a fundamental problem in neuroscience, which often requires the analysis of brain networks derived from functional magnetic resonance imaging…
ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
Mengcheng Lan, Chaofeng Chen, Yiping Ke +3
Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels. While Contrastive Language-Image Pre-tra…
ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference
Mengcheng Lan, Chaofeng Chen, Yiping Ke +3
Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains cha…
Towards Vision-Language Geo-Foundation Model: A Survey
Yue Zhou, Zhihang Zhong, Litong Feng +4
Vision-Language Foundation Models (VLFMs) have made remarkable progress on various multimodal tasks, such as image captioning, image-text retrieval, visual question answering, and…
SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation
Mengcheng Lan, Xinjiang Wang, Yiping Ke +3
Unsupervised semantic segmentation is a challenging task that segments images into semantic groups without manual annotation. Prior works have primarily focused on leveraging prior…
CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning
Qingtian Bian, Jiaxing Xu, Hui Fang +1
The motivations of users to make interactions can be divided into static preference and dynamic interest. To accurately model user representations over time, recent studies in sequ…
Contrastive Graph Pooling for Explainable Classification of Brain Networks
Jiaxing Xu, Qingtian Bian, Xinhang Li +6
Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure neural activation. Its application has been particularly important in identifying underlying ne…