6 papers
CTourLLM: Enhancing LLMs with Chinese Tourism Knowledge
Qikai Wei, Mingzhi Yang, Jinqiang Wang +3
Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the p…
PTMs-TSCIL Pre-Trained Models Based Class-Incremental Learning
Yuanlong Wu, Mingxing Nie, Tao Zhu +3
Class-incremental learning (CIL) for time series data faces critical challenges in balancing stability against catastrophic forgetting and plasticity for new knowledge acquisition,…
A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluations
Jinqiang Wang, Huansheng Ning, Yi Peng +5
Large Language Models (LLMs) have demonstrated surprising performance across various natural language processing tasks. Recently, medical LLMs enhanced with domain-specific knowled…
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer
Shuangjian Li, Tao Zhu, Mingxing Nie +3
Traditional deep learning methods struggle to simultaneously segment, recognize, and forecast human activities from sensor data. This limits their usefulness in many fields such as…
ReLU-KAN: New Kolmogorov-Arnold Networks that Only Need Matrix Addition, Dot Multiplication, and ReLU
Qi Qiu, Tao Zhu, Helin Gong +2
Limited by the complexity of basis function (B-spline) calculations, Kolmogorov-Arnold Networks (KAN) suffer from restricted parallel computing capability on GPUs. This paper propo…
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional Mamba
Shuangjian Li, Tao Zhu, Furong Duan +4
Wearable sensor-based human activity recognition (HAR) is a critical research domain in activity perception. However, achieving high efficiency and long sequence recognition remain…