Multi-hop-qa

This post explores ReaRAG, a novel approach that integrates iterative retrieval-augmented generation (RAG) with knowledge-guided reasoning to improve the factuality and robustness of Large Reasoning Models (LRMs) in multi-hop question answering tasks.

Explore how OPEN-RAG improves reasoning capabilities in Retrieval-Augmented Generation (RAG) using open-source Large Language Models (LLMs), outperforming state-of-the-art models in accuracy and speed.