activity
20232025
most citedMLAD: A Unified Model for Multi-system Log Anomaly Detection

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV2025

TempFlow-GRPO: When Timing Matters for GRPO in Flow Models

Xiaoxuan He, Siming Fu, Yuke Zhao +5

Recent flow matching models for text-to-image generation have achieved remarkable quality, yet their integration with reinforcement learning for human preference alignment remains…

cs.SE2024

ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing

Wei Zhang, Xianfu Cheng, Yi Zhang +8

Log parsing, a vital task for interpreting the vast and complex data produced within software architectures faces significant challenges in the transition from academic benchmarks…

cs.MA2024

mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecture

Wei Zhang, Hongcheng Guo, Jian Yang +8

Root cause analysis (RCA) in Micro-services architecture (MSA) with escalating complexity encounters complex challenges in maintaining system stability and efficiency due to fault…

cs.SE2024

Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging

Wei Zhang, Xiangyuan Guan, Lu Yunhong +5

Logs produced by extensive software systems are integral to monitoring system behaviors. Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults.…

cs.SE20241 cited

MLAD: A Unified Model for Multi-system Log Anomaly Detection

Runqiang Zang, Hongcheng Guo, Jian Yang +6

In spite of the rapid advancements in unsupervised log anomaly detection techniques, the current mainstream models still necessitate specific training for individual system dataset…

cs.LG2024

LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection

Hongcheng Guo, Jian Yang, Jiaheng Liu +7

Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps). Considering log data of variant domains, retraining the whole network fo…