5 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…
Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism
Junfei Zhou, Penglin Dai, Quanmin Wei +3
Multi-agent collaboration enhances the perception capabilities of individual agents through information sharing. However, in real-world applications, differences in sensors and mod…
CoPEFT: Fast Adaptation Framework for Multi-Agent Collaborative Perception with Parameter-Efficient Fine-Tuning
Quanmin Wei, Penglin Dai, Wei Li +2
Multi-agent collaborative perception is expected to significantly improve perception performance by overcoming the limitations of single-agent perception through exchanging complem…
Debunking Free Fusion Myth: Online Multi-view Anomaly Detection with Disentangled Product-of-Experts Modeling
Hao Wang, Zhi-Qi Cheng, Jingdong Sun +4
Multi-view or even multi-modal data is appealing yet challenging for real-world applications. Detecting anomalies in multi-view data is a prominent recent research topic. However,…