1 citations · 1 across the 5 of their papers we have counts for
5 papers
Kelle: Co-design KV Caching and eDRAM for Efficient LLM Serving in Edge Computing
Tianhua Xia, Sai Qian Zhang
Running Large Language Models (LLMs) on edge devices is crucial for reducing latency, improving real-time processing, and enhancing privacy. By performing inference directly on the…
Speculative Decoding and Beyond: An In-Depth Survey of Techniques
Yunhai Hu, Zining Liu, Zhenyuan Dong +3
Sequential dependencies present a fundamental bottleneck in deploying large-scale autoregressive models, particularly for real-time applications. While traditional optimization app…
GazeGen: Gaze-Driven User Interaction for Visual Content Generation
He-Yen Hsieh, Ziyun Li, Sai Qian Zhang +5
We present GazeGen, a user interaction system that generates visual content (images and videos) for locations indicated by the user's eye gaze. GazeGen allows intuitive manipulatio…
Neural Architecture Search of Hybrid Models for NPU-CIM Heterogeneous AR/VR Devices
Yiwei Zhao, Ziyun Li, Win-San Khwa +10
Low-Latency and Low-Power Edge AI is essential for Virtual Reality and Augmented Reality applications. Recent advances show that hybrid models, combining convolution layers (CNN) a…
A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning
Sai Qian Zhang, Jieyu Lin, Qi Zhang
Federated learning (FL) is a training technique that enables client devices to jointly learn a shared model by aggregating locally-computed models without exposing their raw data.…