91 citations · 122 across the 8 of their papers we have counts for
8 papers
AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems
Penglin Dai, Zijie Zhou, Xincao Xu +3
Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and computation constraints. Exist…
FedCoE: Bridging Generalization and Personalization via Federated Coordinated Dual-level MoEs
Penglin Dai, Fulian Li, Xincao Xu +3
Federated Learning (FL) has emerged as a promising paradigm for privacy-preserving distributed learning. However, existing FL methods face a fundamental challenge. Traditional aver…
Quality-Cost Trade-off on Constructing Logical Views for Vehicular Cyber-Physical Systems: A Deep Reinforcement Learning Approach
Junyuan Wu, Xincao Xu, Chuzhao Li +3
With the development of sensing technologies, vehicle-to-everything (V2X) communications, edge computing paradigm, vehicular cyber-physical systems (VCPS) are emerging as the most…
Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach
Xincao Xu, Kai Liu, Penglin Dai +4
Vehicular edge computing (VEC) becomes a promising paradigm for the development of emerging intelligent transportation systems. Nevertheless, the limited resources and massive tran…
Cooperative Sensing and Uploading for Quality-Cost Tradeoff of Digital Twins in VEC
Kai Liu, Xincao Xu, Penglin Dai +1
Recent advances in sensing technologies, wireless communications, and computing paradigms drive the evolution of vehicles in becoming an intelligent and electronic consumer product…
Cooperative Sensing and Heterogeneous Information Fusion in VCPS: A Multi-agent Deep Reinforcement Learning Approach
Xincao Xu, Kai Liu, Penglin Dai +3
Cooperative sensing and heterogeneous information fusion are critical to realize vehicular cyber-physical systems (VCPSs). This paper makes the first attempt to quantitatively meas…
Age of View: A New Metric for Evaluating Heterogeneous Information Fusion in Vehicular Cyber-Physical Systems
Xincao Xu, Kai Liu, Qisen Zhang +3
Heterogeneous information fusion is one of the most critical issues for realizing vehicular cyber-physical systems (VCPSs). This work makes the first attempt at quantitatively meas…
Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration
Xincao Xu, Kai Liu, Ke Xiao +3
Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as…