3 papers
cs.SE2026
GALA: Graph-Augmented LLM Agents for Root Cause Analysis and Incident Response in Microservices
Yifang Tian, Yaming Liu, Zichun Chong +3
Microservice root cause analysis (RCA) requires correlating failures across heterogeneous telemetry within complex service dependency graphs. Existing methods often rely on a singl…
cs.CL2025
FlagEval Findings Report: A Preliminary Evaluation of Large Reasoning Models on Automatically Verifiable Textual and Visual Questions
Bowen Qin, Chen Yue, Fang Yin +26
We conduct a moderate-scale contamination-free (to some extent) evaluation of current large reasoning models (LRMs) with some preliminary findings. We also release ROME, our evalua…
cs.AI2025
GALA: Can Graph-Augmented Large Language Model Agentic Workflows Elevate Root Cause Analysis?
Yifang Tian, Yaming Liu, Zichun Chong +2
Root cause analysis (RCA) in microservice systems is challenging, requiring on-call engineers to rapidly diagnose failures across heterogeneous telemetry such as metrics, logs, and…