Financial QA with LLMs: Domain Knowledge Integration

This paper addresses the limitations of LLMs in financial numerical reasoning by integrating domain-specific knowledge through a multi-retriever RAG system. It highlights the importance of domain-specific training and the trade-offs between hallucination and knowledge gain in LLMs. The study demonstrates SOTA performance improvements, particularly with larger models, and emphasizes the enhanced numerical reasoning capabilities of the latest LLMs.