Abstract

Proposed herein is an enhanced retrieval augmented generation (E-RAG) architecture for use with network automation applications. The enhanced RAG architecture aims to increase RAG performance by reducing the hallucinations of a Large Language Model (LLM) and by decreasing the context length of messages sent to the LLM.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Share

COinS