25 citations · 87 across the 56 of their papers we have counts for
8 papers · 1 filter
Administrative Decentralization in Edge-Cloud Multi-Agent for Mobile Automation
Senyao Li, Zhigang Zuo, Haozhao Wang +3
Collaborative edge-cloud frameworks have emerged as the main- stream paradigm for mobile automation, mitigating the latency and privacy risks inherent to monolithic cloud agents. H…
HALO: Semantic-Aware Distributed LLM Inference in Lossy Edge Network
Peirong Zheng, Wenchao Xu, Haozhao Wang +2
The deployment of large language models' (LLMs) inference at the edge can facilitate prompt service responsiveness while protecting user privacy. However, it is critically challeng…
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
Senyao Li, Haozhao Wang, Wenchao Xu +6
As large language models (LLMs) evolve, deploying them solely in the cloud or compressing them for edge devices has become inadequate due to concerns about latency, privacy, cost,…
Deploying Foundation Model Powered Agent Services: A Survey
Wenchao Xu, Jinyu Chen, Peirong Zheng +8
Foundation model (FM) powered agent services are regarded as a promising solution to develop intelligent and personalized applications for advancing toward Artificial General Intel…
OTAS: An Elastic Transformer Serving System via Token Adaptation
Jinyu Chen, Wenchao Xu, Zicong Hong +4
Transformer model empowered architectures have become a pillar of cloud services that keeps reshaping our society. However, the dynamic query loads and heterogeneous user requireme…
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
Feijie Wu, Song Guo, Haozhao Wang +4
In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training by efficiently utilizin…
Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training
Chengjie Li, Ruixuan Li, Haozhao Wang +4
Distributed asynchronous offline training has received widespread attention in recent years because of its high performance on large-scale data and complex models. As data are dist…
Heterogeneity-aware Gradient Coding for Straggler Tolerance
Haozhao Wang, Song Guo, Bin Tang +2
Gradient descent algorithms are widely used in machine learning. In order to deal with huge volume of data, we consider the implementation of gradient descent algorithms in a distr…