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fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding
Yuxiang Wei, Yanteng Zhang, Xi Xiao +3
Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capability to brain imaging remains la…
Visual Instance-aware Prompt Tuning
Xi Xiao, Yunbei Zhang, Xingjian Li +5
Visual Prompt Tuning (VPT) has emerged as a parameter-efficient fine-tuning paradigm for vision transformers, with conventional approaches utilizing dataset-level prompts that rema…
RoadBench: A Vision-Language Foundation Model and Benchmark for Road Damage Understanding
Xi Xiao, Yunbei Zhang, Janet Wang +9
Accurate road damage detection is crucial for timely infrastructure maintenance and public safety, but existing vision-only datasets and models lack the rich contextual understandi…
MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
Yuxiang Wei, Yanteng Zhang, Xi Xiao +3
Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often priori…
4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer's Diagnosis
Yuxiang Wei, Yanteng Zhang, Xi Xiao +3
Multimodal neuroimaging provides complementary structural and functional insights into both human brain organization and disease-related dynamics. Recent studies demonstrate enhanc…