1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.DC2025
Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices
Shengyuan Ye, Bei Ouyang, Liekang Zeng +4
Generative large language models (LLMs) have garnered significant attention due to their exceptional capabilities in various AI tasks. Traditionally deployed in cloud datacenters,…
cs.DC2024★ 1 cited
Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices
Shengyuan Ye, Liekang Zeng, Xiaowen Chu +2
On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-preserving machine learning at the edge. However, the intensive training workload and limite…
cs.LG2024★ 1 cited
Implementation of Big AI Models for Wireless Networks with Collaborative Edge Computing
Liekang Zeng, Shengyuan Ye, Xu Chen +1
Big Artificial Intelligence (AI) models have emerged as a crucial element in various intelligent applications at the edge, such as voice assistants in smart homes and autonomous ro…