7 citations · 8 across the 6 of their papers we have counts for
8 papers
Decompose Dynamics Before Learning Dependencies in Spatiotemporal Systems
Ziqi Wang, Daojiang Hu, Cheng Bao +4
Relations in networked spatiotemporal systems are often learned from observations that entangle dynamics governed by different mechanisms, obscuring what evolves locally and how it…
When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling
Ziqi Wang, Yuhao Yang, Zhiwei Ling +2
Recent advances in agent and multi-agent systems have shown strong performance on tool use, reasoning, and collaborative tasks. However, existing benchmarks mostly evaluate task co…
ARMOR: A Robust Self-Supervised Framework for Root Cause Analysis in Microservices under Missing Modality
Wenzhuo Qian, Hailiang Zhao, Ziqi Wang +4
Automated incident management is critical for microservice reliability. While recent unified frameworks leverage multimodal data for joint optimization, they unrealistically assume…
Agentic Services Computing
Shuiguang Deng, Hailiang Zhao, Ziqi Wang +6
Services computing has evolved from Web services and microservices to cloud-native and serverless paradigms. These approaches established mature principles for describing, composin…
Learning Intrinsic Water-Quality Dynamics with Rainfall for Data-Driven Forecasting
Ziqi Wang, Hailiang Zhao, Cheng Bao +5
Rainfall is an important environmental driver of water-quality variations through processes such as runoff, pollutant transport, dilution, and resuspension. Traditional mechanistic…
Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation
Wenzhuo Qian, Hailiang Zhao, Jiayi Chen +7
Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the maintenance of strict Service Level Objective…
PeerSync: Accelerating Containerized Service Delivery at the Network Edge
Yinuo Deng, Hailiang Zhao, Dongjing Wang +5
Efficient container image distribution is crucial for enabling machine learning inference at the network edge, where resource limitations and dynamic network conditions create sign…
Decentralized Proactive Model Offloading and Resource Allocation for Split and Federated Learning
Binbin Huang, Hailiang Zhao, Lingbin Wang +3
In the resource-constrained IoT-edge computing environment, Split Federated (SplitFed) learning is implemented to enhance training efficiency. This method involves each terminal de…