5 papers
InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs
Peiliang Gong, Emadeldeen Eldele, Chenyu Liu +8
Large Language Models (LLMs) have recently demonstrated impressive potential for time series forecasting. However, existing methods predominantly rely on passive modality alignment…
Graph Neural Networks in EEG-based Emotion Recognition: A Survey
Chenyu Liu, Yuqiu Deng, Yihao Wu +10
Compared to other modalities, EEG-based emotion recognition can intuitively respond to the emotional patterns in the human brain and, therefore, has become one of the most concerni…
Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery
Xinliang Zhou, Chenyu Liu, Zhisheng Chen +4
Brain foundation models (BFMs) have emerged as a transformative paradigm in computational neuroscience, offering a revolutionary framework for processing diverse neural signals acr…
BiT-MamSleep: Bidirectional Temporal Mamba for EEG Sleep Staging
Xinliang Zhou, Yuzhe Han, Zhisheng Chen +4
In this paper, we address the challenges in automatic sleep stage classification, particularly the high computational cost, inadequate modeling of bidirectional temporal dependenci…
A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective
Chenyu Liu, Xinliang Zhou, Yihao Wu +5
Compared to other modalities, electroencephalogram (EEG) based emotion recognition can intuitively respond to emotional patterns in the human brain and, therefore, has become one o…