46 citations · 176 across the 25 of their papers we have counts for
7 papers · 1 filter
A Memory-Efficient Retrieval Architecture for RAG-Enabled Wearable Medical LLMs-Agents
Zhipeng Liao, Kunming Shao, Jiangnan Yu +5
With powerful and integrative large language models (LLMs), medical AI agents have demonstrated unique advantages in providing personalized medical consultations, continuous health…
Repetitive TMS-based Identification of Methamphetamine-Dependent Individuals Using EEG Spectra
Ziyi Zeng, Yun-Hsuan Chen, Xurong Gao +8
The impact of repetitive transcranial magnetic stimulation (rTMS) on methamphetamine (METH) users' craving levels is often assessed using questionnaires. This study explores the fe…
CSDformer: A Conversion Method for Fully Spike-Driven Transformer
Yuhao Zhang, Chengjun Zhang, Di Wu +2
Spike-based transformer is a novel architecture aiming to enhance the performance of spiking neural networks while mitigating the energy overhead inherent to transformers. However,…
Ultra-Low-Latency Spiking Neural Networks with Temporal-Dependent Integrate-and-Fire Neuron Model for Objects Detection
Chengjun Zhang, Yuhao Zhang, Jie Yang +1
Spiking Neural Networks (SNNs), inspired by the brain, are characterized by minimal power consumption and swift inference capabilities on neuromorphic hardware, and have been widel…
Neuro-MoBRE: Exploring Multi-subject Multi-task Intracranial Decoding via Explicit Heterogeneity Resolving
Di Wu, Yifei Jia, Siyuan Li +3
Neurophysiological decoding, fundamental to advancing brain-computer interface (BCI) technologies, has significantly benefited from recent advances in deep learning. However, exist…
NeuroCLIP: A Multimodal Contrastive Learning Method for rTMS-treated Methamphetamine Addiction Analysis
Chengkai Wang, Di Wu, Yunsheng Liao +10
Methamphetamine dependence poses a significant global health challenge, yet its assessment and the evaluation of treatments like repetitive transcranial magnetic stimulation (rTMS)…
Towards Unified Neural Decoding with Brain Functional Network Modeling
Di Wu, Linghao Bu, Yifei Jia +12
Recent achievements in implantable brain-computer interfaces (iBCIs) have demonstrated the potential to decode cognitive and motor behaviors with intracranial brain recordings; how…