Thesis: Combine Large Language Model With Logical Symbolic Solver for Multi Hop Problems in RAG

This project addresses the challenge of handling multi-hop queries in Retrieval-Augmented Generation (RAG) systems. By integrating a Large Language Model (LLM) with a logical symbolic solver, we aim to enhance reasoning capabilities across diverse pieces of supporting evidence.