Enhancing Retrieval Processes for Language Generation with Augmented Queries

arXiv:2402.16874v1 Announce Type: cross
Abstract: In the rapidly changing world of smart technology, searching for documents has become more challenging due to the rise of advanced language models. These models sometimes face difficulties, like providing inaccurate information, commonly known as "hallucination." This research focuses on addressing this issue through Retrieval-Augmented Generation (RAG), a technique that guides models to give accurate responses based on real facts. To overcome scalability issues, the study explores connecting user queries with sophisticated language models such …

abstract advanced arxiv become cs.ai cs.cl cs.ir documents face hallucination information issue language language generation language models processes queries research retrieval retrieval-augmented searching smart smart technology technology through type world