1 citations · 3 across the 12 of their papers we have counts for
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Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding
Lina Zhang, Tonmoy Monsoor, Peizheng Li +23
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret involuntary, and spatio-temporal…
Deep Models, Shallow Alignment: Uncovering the Granularity Mismatch in Neural Decoding
Yang Du, Siyuan Dai, Yonghao Song +3
Neural visual decoding is a central problem in brain-computer interface research, aiming to reconstruct human visual perception and to elucidate the structure of neural representat…
Why Text Prevails: Vision May Undermine Multimodal Medical Decision Making
Siyuan Dai, Lunxiao Li, Kun Zhao +6
With the rapid progress of large language models (LLMs), advanced multimodal large language models (MLLMs) have demonstrated impressive zero-shot capabilities on vision-language ta…
Zeus: Zero-shot LLM Instruction for Union Segmentation in Multimodal Medical Imaging
Siyuan Dai, Kai Ye, Guodong Liu +2
Medical image segmentation has achieved remarkable success through the continuous advancement of UNet-based and Transformer-based foundation backbones. However, clinical diagnosis…
A Heterogeneous Graph Neural Network Fusing Functional and Structural Connectivity for MCI Diagnosis
Feiyu Yin, Yu Lei, Siyuan Dai +4
Brain connectivity alternations associated with brain disorders have been widely reported in resting-state functional imaging (rs-fMRI) and diffusion tensor imaging (DTI). While ma…
Constrained Multiview Representation for Self-supervised Contrastive Learning
Siyuan Dai, Kai Ye, Kun Zhao +3
Representation learning constitutes a pivotal cornerstone in contemporary deep learning paradigms, offering a conduit to elucidate distinctive features within the latent space and…