36 citations · 69 across the 6 of their papers we have counts for
6 papers
Can AI Agents Detect and Repair Artifact Drift in Network Experiments?
Tianzhu Zhang, Weichen Tao, Changgang Zheng +4
In recent years, AI agents have evolved into capable assistants that carry out multi-step tasks in digital environments. The network systems community is beginning to explore these…
In-Network Market Prediction Using Machine Learning and Limit Order Books
Xinpeng Hong, Changgang Zheng, Joshua Lilley +2
Machine learning is significantly transforming algorithmic trading, yet the requirement for rapid execution speeds persists. While both aspects aim to boost profitability, embeddin…
From Network Automation to Trustworthy Autonomous Networking in the LLM Era: A Network Control Intelligence Perspective
Tianzhu Zhang, Changgang Zheng, Shanshan Wang +5
Since the inception of modern communication networks, the quest for operations automation has never ceased. Yet the evolution of network automation is difficult to characterize wit…
Scalable LLM Agent Tool Access in the Cloud
Mingxin Li, Enge Song, Yueshang Zuo +27
LLM agents increasingly rely on tool calling to act on external systems, and the Model Context Protocol (MCP) has quickly become its de facto interface. Operating MCP at cloud scal…
IIsy: Practical In-Network Classification
Changgang Zheng, Zhaoqi Xiong, Thanh T Bui +6
The rat race between user-generated data and data-processing systems is currently won by data. The increased use of machine learning leads to further increase in processing require…
Automating In-Network Machine Learning
Changgang Zheng, Mingyuan Zang, Xinpeng Hong +4
Using programmable network devices to aid in-network machine learning has been the focus of significant research. However, most of the research was of a limited scope, providing a…