- site: [ARISE Lab@CSE CUHK](http://ariselab.cse.cuhk.edu.hk/index.html) The Chinese University of Hong Kong, Hong Kong SAR, China - [[AIOps]] (Artificial Intelligence for IT Operations) - AIDev (Artificial Intelligence for Development) - RobustAI (Robust Artificial Intelligence) - NLP (Natural Language Processing) ARISE Labの教授（[[Michael R. Lyu]]）によるICSE21の基調講演 - [[Reliability-Driven AIOps for Cloud Resilience - ICSE21 Keynote]] ## Papers - [[2024__ISSRE__Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis]] - LILAC: Log Parsing using LLMs with Adaptive Parsing Cache - [[2024__ICSE__Knowledge-aware Alert Aggregation in Large-scale Cloud Systems - a Hybrid Approach]] - [[2024__ICSE__FaultProfIT - Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems]] - [[2024__TOSEM__HeMiRCA - Fine-Grained Root Cause Analysis for Microservices with Heterogeneous Data Sources]] - [[2023__ISSRE__Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services]] - [[2023__ASE__Prism - Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems]] - [[2023__ICDM__A Roadmap towards Intelligent Operations for Reliable Cloud Computing Systems]] - [[2023__ASE__AutoLog - A Log Sequence Synthesis Framework for Anomaly Detection]] - [[2023__arXiv__A Large-scale Benchmark for Log Parsing]] - [[2023__arXiv__Scalable and Adaptive Log-based Anomaly Detection with Expert in the Loop]] - [[2023__ICSE__Eadro - An End-to-End Troubleshooting Framework for Microservices on Multi-source Data]] - [[2023__arXiv__Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention]] - [[2022__ICSE__Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching]] - [[2022__arXiv__Heterogeneous Anomaly Detection for Software Systems via Attentive Multi-modal Learning]] - [[2022__OSR__An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection]]