Owl: A large language model for it operations
With the rapid development of IT operations, it has become increasingly crucial to efficiently
manage and analyze large volumes of data for practical applications. The techniques of …
manage and analyze large volumes of data for practical applications. The techniques of …
Large language models in cybersecurity: State-of-the-art
The rise of Large Language Models (LLMs) has revolutionized our comprehension of
intelligence bringing us closer to Artificial Intelligence. Since their introduction, researchers …
intelligence bringing us closer to Artificial Intelligence. Since their introduction, researchers …
[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arXiv preprint arXiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
Llmparser: A llm-based log parsing framework
The process of log parsing, which converts log messages into structured formats, is a crucial
step for various log analysis tasks. Although numerous log parsers have been proposed …
step for various log analysis tasks. Although numerous log parsers have been proposed …
A review of advancements and applications of pre-trained language models in cybersecurity
Z Liu - 2024 12th International Symposium on Digital …, 2024 - ieeexplore.ieee.org
In this paper, we delve into the transformative role of pre-trained language models (PLMs) in
cybersecurity, offering a comprehensive examination of their deployment across a wide …
cybersecurity, offering a comprehensive examination of their deployment across a wide …
LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
Log parsing transforms log messages into structured formats, serving as the prerequisite
step for various log analysis tasks. Although a variety of log parsing approaches have been …
step for various log analysis tasks. Although a variety of log parsing approaches have been …
Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging
Logs produced by extensive software systems are integral to monitoring system behaviors.
Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults. Log …
Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults. Log …
RAGLog: Log Anomaly Detection using Retrieval Augmented Generation
J Pan, SL Wong, Y Yuan - arXiv preprint arXiv:2311.05261, 2023 - arxiv.org
The ability to detect log anomalies from system logs is a vital activity needed to ensure cyber
resiliency of systems. It is applied for fault identification or facilitate cyber investigation and …
resiliency of systems. It is applied for fault identification or facilitate cyber investigation and …
ULog: Unsupervised Log Parsing with Large Language Models through Log Contrastive Units
Log parsing serves as an essential prerequisite for various log analysis tasks. Recent
advancements in this field have improved parsing accuracy by leveraging the semantics in …
advancements in this field have improved parsing accuracy by leveraging the semantics in …
Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection
Time series anomaly detection (TSAD) plays a crucial role in various industries by
identifying atypical patterns that deviate from standard trends, thereby maintaining system …
identifying atypical patterns that deviate from standard trends, thereby maintaining system …