RAAD-LLM: Adaptive Anomaly Detection Using LLMs and RAG Integration

no code implementations • 4 Mar 2025 • Alicia Russell-Gilbert, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jabour, Thomas Arnold, Joshua Church

Anomaly detection in complex industrial environments poses unique challenges, particularly in contexts characterized by data sparsity and evolving operational conditions.

Anomaly Detection RAG

AAD-LLM: Adaptive Anomaly Detection Using Large Language Models

no code implementations • 1 Nov 2024 • Alicia Russell-Gilbert, Alexander Sommers, Andrew Thompson, Logan Cummins, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jaboure, Thomas Arnold, Joshua Church

The research aims to improve the transferability of anomaly detection models by leveraging Large Language Models (LLMs) and seeks to validate the enhanced effectiveness of the proposed approach in data-sparse industrial applications.

Anomaly Detection