20 citations · 51 across the 25 of their papers we have counts for
14 papers · 1 filter
Generality Is Not Enough: Zero-Label Cross-System Log-Based Anomaly Detection via Knowledge-Level Collaboration
Xinlong Zhao, Tong Jia, Minghua He +1
Log-based anomaly detection is crucial for ensuring software system stability. However, the scarcity of labeled logs limits rapid deployment to new systems. Cross-system transfer h…
ZeroLog: Zero-Label Generalizable Cross-System Log-based Anomaly Detection
Xinlong Zhao, Tong Jia, Minghua He +2
Log-based anomaly detection is an important task in ensuring the stability and reliability of software systems. One of the key problems in this task is the lack of labeled logs. Ex…
MicroRemed: Benchmarking LLMs in Microservices Remediation
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +6
Large Language Models (LLMs) integrated with agent-based reasoning frameworks have recently shown strong potential for autonomous decision-making and system-level operations. One p…
FusionLog: Cross-System Log-based Anomaly Detection via Fusion of General and Proprietary Knowledge
Xinlong Zhao, Tong Jia, Minghua He +2
Log-based anomaly detection is critical for ensuring the stability and reliability of web systems. One of the key problems in this task is the lack of sufficient labeled logs, whic…
LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptation
Chiming Duan, Minghua He, Pei Xiao +11
Log-based anomaly detection is a essential task for ensuring the reliability and performance of software systems. However, the performance of existing anomaly detection methods hea…
United We Stand: Towards End-to-End Log-based Fault Diagnosis via Interactive Multi-Task Learning
Minghua He, Chiming Duan, Pei Xiao +8
Log-based fault diagnosis is essential for maintaining software system availability. However, existing fault diagnosis methods are built using a task-independent manner, which fail…
Walk the Talk: Is Your Log-based Software Reliability Maintenance System Really Reliable?
Minghua He, Tong Jia, Chiming Duan +6
Log-based software reliability maintenance systems are crucial for sustaining stable customer experience. However, existing deep learning-based methods represent a black box for se…
Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought
Lingzhe Zhang, Tong Jia, Kangjin Wang +4
As contemporary microservice systems become increasingly popular and complex-often comprising hundreds or even thousands of fine-grained, interdependent subsystems-they are facing…
From Few-Label to Zero-Label: An Approach for Cross-System Log-Based Anomaly Detection with Meta-Learning
Xinlong Zhao, Tong Jia, Minghua He +3
Log anomaly detection plays a critical role in ensuring the stability and reliability of software systems. However, existing approaches rely on large amounts of labeled log data, w…
A Survey of AIOps in the Era of Large Language Models
Lingzhe Zhang, Tong Jia, Mengxi Jia +7
As large language models (LLMs) grow increasingly sophisticated and pervasive, their application to various Artificial Intelligence for IT Operations (AIOps) tasks has garnered sig…
LogDB: Multivariate Log-based Failure Diagnosis for Distributed Databases (Extended from MultiLog)
Lingzhe Zhang, Tong Jia, Mengxi Jia +1
Distributed databases, as the core infrastructure software for internet applications, play a critical role in modern cloud services. However, existing distributed databases frequen…
AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +3
Distributed databases are critical infrastructures for today's large-scale software systems, making effective failure management essential to ensure software availability. However,…
ThinkFL: Self-Refining Failure Localization for Microservice Systems via Reinforcement Fine-Tuning
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +6
As modern microservice systems grow increasingly popular and complex-often consisting of hundreds or even thousands of fine-grained, interdependent components-they are becoming mor…
Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis
Xixuan Yang, Xin Huang, Chiming Duan +4
Anomaly detection is crucial for ensuring the stability and reliability of web service systems. Logs and metrics contain multiple information that can reflect the system's operatio…