FT-RAG: A Fine-grained Retrieval-Augmented Generation Framework for Complex Table Reasoning

arXiv:2605.01495v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding responses in external knowledge during inference. However, conventiona RAG systems under-perform on structured tabular data, largely due to coarse retrieval...