Large language models for cyber security: A systematic literature review

HX Xu, SA Wang, N Li, K Wang, Y Zhao, K Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid advancement of Large Language Models (LLMs) has opened up new
opportunities for leveraging artificial intelligence in various domains, including cybersecurity …

Everything of thoughts: Defying the law of penrose triangle for thought generation

R Ding, C Zhang, L Wang, Y Xu, M Ma… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent advancements in Large Language Models (LLMs) have revolutionized decision-
making by breaking down complex problems into more manageable language sequences …

Imdiffusion: Imputed diffusion models for multivariate time series anomaly detection

Y Chen, C Zhang, M Ma, Y Liu, R Ding, B Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Anomaly detection in multivariate time series data is of paramount importance for ensuring
the efficient operation of large-scale systems across diverse domains. However, accurately …

Xpert: Empowering incident management with query recommendations via large language models

Y Jiang, C Zhang, S He, Z Yang, M Ma, S Qin… - Proceedings of the …, 2024 - dl.acm.org
Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents
occurring within these systems can lead to service disruptions and adversely affect user …

Llmparser: An exploratory study on using large language models for log parsing

Z Ma, AR Chen, DJ Kim, TH Chen, S Wang - Proceedings of the IEEE …, 2024 - dl.acm.org
Logs are important in modern software development with runtime information. Log parsing is
the first step in many log-based analyses, that involve extracting structured information from …

Rcagent: Cloud root cause analysis by autonomous agents with tool-augmented large language models

Z Wang, Z Liu, Y Zhang, A Zhong, J Wang… - Proceedings of the 33rd …, 2024 - dl.acm.org
Large language model (LLM) applications in cloud root cause analysis (RCA) have been
actively explored recently. However, current methods are still reliant on manual workflow …

Face it yourselves: An llm-based two-stage strategy to localize configuration errors via logs

S Shan, Y Huo, Y Su, Y Li, D Li, Z Zheng - Proceedings of the 33rd ACM …, 2024 - dl.acm.org
Configurable software systems are prone to configuration errors, resulting in significant
losses to companies. However, diagnosing these errors is challenging due to the vast and …

Configuration validation with large language models

X Lian, Y Chen, R Cheng, J Huang, P Thakkar… - arXiv preprint arXiv …, 2023 - arxiv.org
Misconfigurations are major causes of software failures. Existing practices rely on developer-
written rules or test cases to validate configurations, which are expensive. Machine learning …

Ufo: A ui-focused agent for windows os interaction

C Zhang, L Li, S He, X Zhang, B Qiao, S Qin… - arXiv preprint arXiv …, 2024 - arxiv.org
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to
applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a …

Failure Diagnosis in Microservice Systems: A Comprehensive Survey and Analysis

S Zhang, S Xia, W Fan, B Shi, X Xiong, Z Zhong… - arXiv preprint arXiv …, 2024 - arxiv.org
Modern microservice systems have gained widespread adoption due to their high
scalability, flexibility, and extensibility. However, the characteristics of independent …