Saved in:
| Main Authors: | Yang, Lin, Chen, Junjie, Gao, Shutao, Gong, Zhihao, Zhang, Hongyu, Kang, Yue, Li, Huaan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2308.12612 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LogSD: Detecting Anomalies from System Logs through Self-supervised Learning and Frequency-based Masking
by: Xie, Yongzheng, et al.
Published: (2024)
by: Xie, Yongzheng, et al.
Published: (2024)
Multivariate Log-based Anomaly Detection for Distributed Database
by: Zhang, Lingzhe, et al.
Published: (2024)
by: Zhang, Lingzhe, et al.
Published: (2024)
LogLLM: Log-based Anomaly Detection Using Large Language Models
by: Guan, Wei, et al.
Published: (2024)
by: Guan, Wei, et al.
Published: (2024)
On the Effectiveness of Log Representation for Log-based Anomaly Detection
by: Wu, Xingfang, et al.
Published: (2023)
by: Wu, Xingfang, et al.
Published: (2023)
Practitioners' Expectations on Log Anomaly Detection
by: Ma, Xiaoxue, et al.
Published: (2024)
by: Ma, Xiaoxue, et al.
Published: (2024)
ZeroLog: Zero-Label Generalizable Cross-System Log-based Anomaly Detection
by: Zhao, Xinlong, et al.
Published: (2025)
by: Zhao, Xinlong, et al.
Published: (2025)
A Comparative Study of Semantic Log Representations for Software Log-based Anomaly Detection
by: Wang, Yuqing, et al.
Published: (2026)
by: Wang, Yuqing, et al.
Published: (2026)
On the Evaluation of Large Language Models in Unit Test Generation
by: Yang, Lin, et al.
Published: (2024)
by: Yang, Lin, et al.
Published: (2024)
Improving Smart Contract Security with Contrastive Learning-based Vulnerability Detection
by: Chen, Yizhou, et al.
Published: (2024)
by: Chen, Yizhou, et al.
Published: (2024)
LUNAR: Unsupervised LLM-based Log Parsing
by: Huang, Junjie, et al.
Published: (2024)
by: Huang, Junjie, et al.
Published: (2024)
FusionLog: Cross-System Log-based Anomaly Detection via Fusion of General and Proprietary Knowledge
by: Zhao, Xinlong, et al.
Published: (2025)
by: Zhao, Xinlong, et al.
Published: (2025)
LogICL: Distilling LLM Reasoning to Bridge the Semantic Gap in Cross-Domain Log Anomaly Detection
by: Ye, Jingwei, et al.
Published: (2025)
by: Ye, Jingwei, et al.
Published: (2025)
Cross-System Software Log-based Anomaly Detection Using Meta-Learning
by: Wang, Yuqing, et al.
Published: (2024)
by: Wang, Yuqing, et al.
Published: (2024)
Detecting Anomalies in Software Execution Logs with Siamese Network
by: Hashemi, Shayan, et al.
Published: (2021)
by: Hashemi, Shayan, et al.
Published: (2021)
LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs
by: Yamanaka, Yuuki, et al.
Published: (2024)
by: Yamanaka, Yuuki, et al.
Published: (2024)
Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study
by: Zhang, Lingzhe, et al.
Published: (2024)
by: Zhang, Lingzhe, et al.
Published: (2024)
CodeAD: Synthesize Code of Rules for Log-based Anomaly Detection with LLMs
by: Huang, Junjie, et al.
Published: (2025)
by: Huang, Junjie, et al.
Published: (2025)
AnomalyGen: An Automated Semantic Log Sequence Generation Framework with LLM for Anomaly Detection
by: Li, Xinyu, et al.
Published: (2025)
by: Li, Xinyu, et al.
Published: (2025)
AnomalyGen: Enhancing Log-Based Anomaly Detection with Code-Guided Data Augmentation
by: Li, Xinyu, et al.
Published: (2026)
by: Li, Xinyu, et al.
Published: (2026)
Impact of Log Parsing on Deep Learning-Based Anomaly Detection
by: Khan, Zanis Ali, et al.
Published: (2023)
by: Khan, Zanis Ali, et al.
Published: (2023)
LogPurge: Log Data Purification for Anomaly Detection via Rule-Enhanced Filtering
by: Zhang, Shenglin, et al.
Published: (2025)
by: Zhang, Shenglin, et al.
Published: (2025)
Speed and Performance of Parserless and Unsupervised Anomaly Detection Methods on Software Logs
by: Nyyssölä, Jesse, et al.
Published: (2023)
by: Nyyssölä, Jesse, et al.
Published: (2023)
LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs
by: Hadadi, Fatemeh, et al.
Published: (2024)
by: Hadadi, Fatemeh, et al.
Published: (2024)
OneLog: Towards End-to-End Training in Software Log Anomaly Detection
by: Hashemi, Shayan, et al.
Published: (2021)
by: Hashemi, Shayan, et al.
Published: (2021)
Improving Compiler Bug Isolation by Leveraging Large Language Models
by: Qi, Yixian, et al.
Published: (2025)
by: Qi, Yixian, et al.
Published: (2025)
Graph Neural Networks based Log Anomaly Detection and Explanation
by: Li, Zhong, et al.
Published: (2023)
by: Li, Zhong, et al.
Published: (2023)
LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection
by: Guo, Hongcheng, et al.
Published: (2024)
by: Guo, Hongcheng, et al.
Published: (2024)
OMLog: Online Log Anomaly Detection for Evolving System with Meta-learning
by: Tian, Jiyu, et al.
Published: (2024)
by: Tian, Jiyu, et al.
Published: (2024)
LogLM: From Task-based to Instruction-based Automated Log Analysis
by: Liu, Yilun, et al.
Published: (2024)
by: Liu, Yilun, et al.
Published: (2024)
Beyond Window-Based Detection: A Graph-Centric Framework for Discrete Log Anomaly Detection
by: Qi, Jiaxing, et al.
Published: (2025)
by: Qi, Jiaxing, et al.
Published: (2025)
AUCAD: Automated Construction of Alignment Dataset from Log-Related Issues for Enhancing LLM-based Log Generation
by: Zhang, Hao, et al.
Published: (2024)
by: Zhang, Hao, et al.
Published: (2024)
On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations
by: Ma, Xiaoxue, et al.
Published: (2024)
by: Ma, Xiaoxue, et al.
Published: (2024)
ASTD Patterns for Integrated Continuous Anomaly Detection In Data Logs
by: Jabri, Chaymae El, et al.
Published: (2024)
by: Jabri, Chaymae El, et al.
Published: (2024)
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
by: Jiang, Zhihan, et al.
Published: (2023)
by: Jiang, Zhihan, et al.
Published: (2023)
Stronger, Cheaper and Demonstration-Free Log Parsing with LLMs
by: Xiao, Yi, et al.
Published: (2024)
by: Xiao, Yi, et al.
Published: (2024)
ASGNet: Adaptive Semantic Gate Networks for Log-Based Anomaly Diagnosis
by: Yang, Haitian, et al.
Published: (2024)
by: Yang, Haitian, et al.
Published: (2024)
LogLead -- Fast and Integrated Log Loader, Enhancer, and Anomaly Detector
by: Mäntylä, Mika, et al.
Published: (2023)
by: Mäntylä, Mika, et al.
Published: (2023)
Log-based, Business-aware REST API Testing
by: Yang, Ding, et al.
Published: (2026)
by: Yang, Ding, et al.
Published: (2026)
A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection
by: Ali, Shan, et al.
Published: (2023)
by: Ali, Shan, et al.
Published: (2023)
FedLAD: A Modular and Adaptive Testbed for Federated Log Anomaly Detection
by: Liao, Yihan, et al.
Published: (2025)
by: Liao, Yihan, et al.
Published: (2025)
Similar Items
-
LogSD: Detecting Anomalies from System Logs through Self-supervised Learning and Frequency-based Masking
by: Xie, Yongzheng, et al.
Published: (2024) -
Multivariate Log-based Anomaly Detection for Distributed Database
by: Zhang, Lingzhe, et al.
Published: (2024) -
LogLLM: Log-based Anomaly Detection Using Large Language Models
by: Guan, Wei, et al.
Published: (2024) -
On the Effectiveness of Log Representation for Log-based Anomaly Detection
by: Wu, Xingfang, et al.
Published: (2023) -
Practitioners' Expectations on Log Anomaly Detection
by: Ma, Xiaoxue, et al.
Published: (2024)