1 citations · 1 across the 14 of their papers we have counts for
16 papers
VisCache: Visual KV Cache Pruning for Efficient Vision Large Language Model Inference
Lyuke Wang, Zhuo Li, Guangxu Zhu
While Vision Large Language Models (VLLMs) have achieved remarkable success in multimodal reasoning, their long-context inference remains prohibitively expensive due to the massive…
AirMoE: Statistic-Augmented Over-the-Air MoE for Collaborative Intelligence
Wei-Bin Kou, Jingreng Lei, Guangxu Zhu +1
Mixture of Experts (MoE) are increasingly deployed over wireless cloud-edge networks, as a single edge device lacks sufficient resources to host large-scale models locally. In this…
The Universal Language of CSI:Unifying Wireless Sensing Across Devices and Environments
Jiayi Chen, Weiting Ou, Guangxu Zhu
WiFi sensing based on Channel State Information (CSI) promises ubiquitous, device-free perception, yet current research remains trapped in a Tower of Babel - fragmented into isolat…
Bridging Large-Model Reasoning and Real-Time Control via Agentic Fast-Slow Planning
Jiayi Chen, Shuai Wang, Guangxu Zhu +1
Large foundation models enable powerful reasoning for autonomous systems, but mapping semantic intent to reliable real-time control remains challenging. Existing approaches either…
FedDSR: Federated Deep Supervision and Regularization Towards Autonomous Driving
Wei-Bin Kou, Guangxu Zhu, Bingyang Cheng +3
Federated Learning (FL) enables collaborative training of autonomous driving (AD) models across distributed vehicles while preserving data privacy. However, FL encounters critical…
Statistic-Augmented, Decoupled MoE Routing and Aggregating in Autonomous Driving
Wei-Bin Kou, Guangxu Zhu, Jingreng Lei +3
Autonomous driving (AD) scenarios are inherently complex and diverse, posing significant challenges for a single deep learning model to effectively cover all possible conditions, s…