activity
20242026
collaborators

10 papers

cs.CV2026

NeuroAlign: Hierarchical Multimodal Fusion of Dynamic and Structural Neuroimaging for MCI Analysis

Xiongri Shen, Zhenxi Song, Jiaqi wang +13

Multimodal neuroimaging fusion of functional MRI (fMRI) and diffusion tensor imaging (DTI) provides complementary information for cognitive impairment analysis, but remains challen…

cs.AI2026

Brain-Atlas-Guided Generative Counterfactual Attention for Explainable Cognitive Decline Diagnosis Using Multimodal Connectomes

Xiongri Shen, Jiaqi Wang, Zhenxi Song +5

Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are closely associated with the early Alzheimer's disease continuum, where accurate and explainable diagnosis…

eess.SP2026

EEG-MACS: Manifold Attention and Confidence Stratification for EEG-based Cross-Center Brain Disease Diagnosis under Unreliable Annotations

Zhenxi Song, Ruihan Qin, Huixia Ren +4

Cross-center data heterogeneity and annotation unreliability significantly challenge the intelligent diagnosis of diseases using brain signals. A notable example is the EEG-based d…

cs.SD2026

SpikCommander: A High-performance Spiking Transformer with Multi-view Learning for Efficient Speech Command Recognition

Jiaqi Wang, Liutao Yu, Xiongri Shen +6

Spiking neural networks (SNNs) offer a promising path toward energy-efficient speech command recognition (SCR) by leveraging their event-driven processing paradigm. However, existi…

cs.HC2025

Senti-iFusion: An Integrity-centered Hierarchical Fusion Framework for Multimodal Sentiment Analysis under Uncertain Modality Missingness

Liling Li, Guoyang Xu, Xiongri Shen +4

Multimodal Sentiment Analysis (MSA) is critical for human-computer interaction but faces challenges when the modalities are incomplete or missing. Existing methods often assume pre…

cs.LG2025

SM-Former: Spiking Symmetric Mixing Branchformer for Brain Auditory Attention Detection

Jiaqi Wang, Zhengyu Ma, Xiongri Shen +7

Auditory attention detection (AAD) aims to decode listeners' focus in complex auditory environments from electroencephalography (EEG) recordings, which is crucial for developing ne…