1 citations · 1 across the 4 of their papers we have counts for
4 papers
FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning
Yuan Yao, Lixu Wang, Jiaqi Wu +7
Federated learning (FL) enables collaborative training across clients while preserving privacy. While most existing FL methods assume homogeneous model architectures, client hetero…
Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment
Jiaqi Wu, Shihao Zhang, Simin Chen +7
Edge computing has emerged as a key paradigm for deploying deep learning-based object detection in time-sensitive scenarios. However, existing edge detection methods face challenge…
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
Jiaqi Wu, Simin Chen, Yuzhe Yang +6
In recent years, large language models (LLMs) have significantly advanced the field of natural language processing (NLP). By fine-tuning LLMs with data from specific scenarios, the…
Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment
Jiaqi Wu, Simin Chen, Zehua Wang +4
As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this b…