{"total":35,"rows":[{"id":"2108.01955","title":"Log-based Anomaly Detection Without Log Parsing","created":"2021-08-04","cited_by_count":59,"area":null},{"id":"2202.04301","title":"Log-based Anomaly Detection with Deep Learning: How Far Are We?","created":"2022-02-09","cited_by_count":57,"area":null},{"id":"2107.05908","title":"Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection","created":"2021-07-13","cited_by_count":37,"area":null},{"id":"2309.01189","title":"LogGPT: Exploring ChatGPT for Log-Based Anomaly Detection","created":"2023-09-03","cited_by_count":35,"area":null},{"id":"2111.09564","title":"LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model","created":"2021-11-18","cited_by_count":30,"area":null},{"id":"2207.03820","title":"Deep Learning for Anomaly Detection in Log Data: A Survey","created":"2022-07-08","cited_by_count":28,"area":null},{"id":"2304.10550","title":"Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review","created":"2023-04-19","cited_by_count":21,"area":null},{"id":"2304.04661","title":"AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges","created":"2023-04-10","cited_by_count":15,"area":null},{"id":"2102.11570","title":"Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models","created":"2021-02-23","cited_by_count":12,"area":null},{"id":"2109.09537","title":"A2Log: Attentive Augmented Log Anomaly Detection","created":"2021-09-20","cited_by_count":10,"area":null},{"id":"2101.06054","title":"Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper","created":"2021-01-15","cited_by_count":7,"area":null},{"id":"2104.07324","title":"OneLog: Towards End-to-End Training in Software Log Anomaly Detection","created":"2021-04-15","cited_by_count":7,"area":null},{"id":"2111.01657","title":"LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision","created":"2021-11-02","cited_by_count":6,"area":null},{"id":"2308.08736","title":"On the Effectiveness of Log Representation for Log-based Anomaly Detection","created":"2023-08-17","cited_by_count":6,"area":null},{"id":"2409.13561","title":"Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis","created":"2024-09-20","cited_by_count":6,"area":null},{"id":"2402.10397","title":"LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs","created":"2024-02-16","cited_by_count":4,"area":null},{"id":"2404.08750","title":"FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and Discrimination","created":"2024-04-12","cited_by_count":4,"area":null},{"id":"2301.10681","title":"PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning","created":"2023-01-25","cited_by_count":3,"area":null},{"id":"2301.13415","title":"LogAI: A Library for Log Analytics and Intelligence","created":"2023-01-31","cited_by_count":2,"area":null},{"id":"2409.01909","title":"LUK: Empowering Log Understanding with Expert Knowledge from Large Language Models","created":"2024-09-03","cited_by_count":2,"area":null},{"id":"2505.13496","title":"ADALog: Adaptive Unsupervised Anomaly detection in Logs with Self-attention Masked Language Model","created":"2025-05-15","cited_by_count":2,"area":null},{"id":"2207.03206","title":"Leveraging Log Instructions in Log-based Anomaly Detection","created":"2022-07-07","cited_by_count":1,"area":null},{"id":"2203.10960","title":"AI based Log Analyser: A Practical Approach","created":"2022-03-18","cited_by_count":0,"area":null},{"id":"2204.02636","title":"Failure Identification from Unstable Log Data using Deep Learning","created":"2022-04-06","cited_by_count":0,"area":null},{"id":"2307.03359","title":"CSCLog: A Component Subsequence Correlation-Aware Log Anomaly Detection Method","created":"2023-07-07","cited_by_count":0,"area":null},{"id":"2311.05160","title":"RAPID: Training-free Retrieval-based Log Anomaly Detection with PLM considering Token-level information","created":"2023-11-09","cited_by_count":0,"area":null},{"id":"2409.20503","title":"What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach","created":"2024-09-30","cited_by_count":0,"area":null},{"id":"2411.15250","title":"TPLogAD: Unsupervised Log Anomaly Detection Based on Event Templates and Key Parameters","created":"2024-11-22","cited_by_count":0,"area":null},{"id":"2510.11141","title":"A Comprehensive Forecasting-Based Framework for Time Series Anomaly Detection: Benchmarking on the Numenta Anomaly Benchmark (NAB)","created":"2025-10-13","cited_by_count":0,"area":null},{"id":"2511.14062","title":"LogPurge: Log Data Purification for Anomaly Detection via Rule-Enhanced Filtering","created":"2025-11-18","cited_by_count":0,"area":null},{"id":"2512.23380","title":"A unified framework for detecting point and collective anomalies in operating system logs via collaborative transformers","created":"2025-12-29","cited_by_count":0,"area":null},{"id":"2602.07303","title":"KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction","created":"2026-02-07","cited_by_count":0,"area":null},{"id":"2606.08649","title":"Sample-Efficient LLM-Based Detection of Malicious Web Server Logs with Forensically Explainable Reasoning","created":"2026-06-07","cited_by_count":0,"area":null},{"id":"2608.00651","title":"Understanding Online Failure Prediction in Linux Through Complementary Multi-View Explainability","created":"2026-08-01","cited_by_count":0,"area":null},{"id":"2608.17965","title":"Too Sure to Be Safe: Model Calibration for Reliable Log Anomaly Detection","created":"2026-08-18","cited_by_count":0,"area":null}],"next_cursor":null}