3 papers
cs.AI2026
TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices
Junle Wang, Xingchuang Liao, Wenjun Wu
Root cause analysis (RCA) in microservices is challenging due to (i) noisy and heterogeneous multimodal observability (metrics, logs, traces), (ii) cascading failure propagation th…
cs.AI2026
STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices
Junle Wang, Xingchuang Liao, Wenjun Wu
LLM-based root cause analysis (RCA) agents have recently emerged as a promising paradigm for incident diagnosis in microservice AIOps. However, their reliability remains fragile: a…
cs.CL2025
CoE-Ops: Collaboration of LLM-based Experts for AIOps Question-Answering
Jinkun Zhao, Yuanshuai Wang, Xingjian Zhang +6
With the rapid evolution of artificial intelligence, AIOps has emerged as a prominent paradigm in DevOps. Lots of work has been proposed to improve the performance of different AIO…