5 papers
Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection
Jinyu Li, Xiao Wei, Bin Wen +5
Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in patholo…
Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
Xiao Wei, Bin Wen, Yuqin Lin +5
Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression. While AI-based speech detection is non-invasive and cost-effective, it faces a critical data ef…
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework
Xiao Wei, Xiaobao Wang, Ning Zhuang +3
Intent detection aims to identify user intents from natural language inputs, where supervised methods rely heavily on labeled in-domain (IND) data and struggle with out-of-domain (…
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective
Di Jin, Jingyi Cao, Xiaobao Wang +4
Graph anomaly detection aims to identify unusual patterns in graph-based data, with wide applications in fields such as web security and financial fraud detection. Existing methods…
Enriching Multimodal Sentiment Analysis through Textual Emotional Descriptions of Visual-Audio Content
Sheng Wu, Xiaobao Wang, Longbiao Wang +2
Multimodal Sentiment Analysis (MSA) stands as a critical research frontier, seeking to comprehensively unravel human emotions by amalgamating text, audio, and visual data. Yet, dis…