EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations

This article, sourced from ArXiv, focuses on evaluating the robustness of Retrieval-Augmented Generation (RAG) models. The title suggests an investigation into how well RAG systems perform when subjected to symbolic perturbations, which likely involves altering the input data in a systematic way to test the model's resilience. The research area is clearly within the domain of Large Language Models (LLMs) and their practical application.