20 citations · 25 across the 8 of their papers we have counts for
9 papers
RespFocus: Learning Temporal Evidence for Weakly Supervised Respiratory Sound Classification
Yi Tian, Xiaohuan Chen, Yufei tang +5
Respiratory auscultation provides a low-cost means of assessing pulmonary function, yet transient crackles and sustained wheezes can be difficult to recognize in noisy clinical rec…
Training-Free Token-Level Steering for LLM Personalized Co-Writing
Wenhao Mao, Chengbin Hou, Weixiao Wang +4
While Large Language Models (LLMs) show great promise for personalization, they often lack specialized domain knowledge. Conventional solutions like fine-tuning struggle with high…
Enhancing Noise Robustness of Parkinson's Disease Telemonitoring via Contrastive Feature Augmentation
Ziming Tang, Chengbin Hou, Tianyu Zhang +3
Parkinson's disease (PD) is one of the most common neurodegenerative disorder. PD telemonitoring emerges as a novel assessment modality enabling self-administered at-home tests of…
FedAGHN: Personalized Federated Learning with Attentive Graph HyperNetworks
Jiarui Song, Yunheng Shen, Chengbin Hou +4
Personalized Federated Learning (PFL) aims to address the statistical heterogeneity of data across clients by learning the personalized model for each client. Among various PFL app…
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection
Hanzhe Liang, Guoyang Xie, Chengbin Hou +3
3D anomaly detection has recently become a significant focus in computer vision. Several advanced methods have achieved satisfying anomaly detection performance. However, they typi…
Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs
Xinyu Lin, Tianyu Zhang, Chengbin Hou +3
Node Importance Estimation (NIE) is a task that quantifies the importance of node in a graph. Recent research has investigated to exploit various information from Knowledge Graphs…
Parse Trees Guided LLM Prompt Compression
Wenhao Mao, Chengbin Hou, Tianyu Zhang +3
Offering rich contexts to Large Language Models (LLMs) has shown to boost the performance in various tasks, but the resulting longer prompt would increase the computational cost an…
Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models
Tianyu Zhang, Yuxiang Ren, Chengbin Hou +2
Molecular property prediction is a crucial foundation for drug discovery. In recent years, pre-trained deep learning models have been widely applied to this task. Some approaches t…
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning
Hongze Zhu, Guoyang Xie, Chengbin Hou +4
High-resolution point clouds~(HRPCD) anomaly detection~(AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods th…