Analyzing performance of Retrieval Augmented Generation models for Question Answering Tasks.

arXiv:2610.20419v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) models have become almost a cornerstone of open-domain question answering tasks; in which the quality of answers generated in the process, greatly relies on the effe