Using Self-Organizing Map To Bolster Retrieval-Augmented Generation In Large Language Models

SOM is proposed to bolster efficient retrieval of LLM context for RAG…

Background

Large volumes of data are used to train Large Language Models (LLM) containing millions and billions of model parameters with the goal of text generation, such as text completion, text summarization, language translations, and answering questions. While LLMs develop a knowledge base per se from the training data sources, there is always a cut-off training date post which LLM will not …

deep-dives large language models retrieval-augmented-gen self-organizing-map vector database