3 papers
cs.SE2026
Rethinking Tool Design for Agentic RCA: A Controlled Empirical Study
Yu Luo, Rongchen Gao, Zhenhui Zhou +7
Large language model (LLM) agents are increasingly explored for root cause analysis (RCA) in microservice systems, yet empirical guidance on how to design and combine their tools r…
cs.AI2026
OpsMem: Dual-Memory Reasoning with Cross-Memory Resonance for Failure Diagnosis
Yongqian Sun, Rongchen Gao, Yu Luo +6
Failure diagnosis in modern software systems requires iterative evidence acquisition and hypothesis reasoning guided by operational experience. Existing LLM-based methods improve d…
cs.AI2026
Graph of States: Solving Abductive Tasks with Large Language Models
Yu Luo, Rongchen Gao, Lu Teng +9
Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former two, abductive reasoning remains…