Financial RAG Answer Quality Regression with Table-Text Evidence Features on RAGBench FinQA and eManual

Financial retrieval-augmented generation (RAG) systems must answer questions that combine narrative disclosures, tabular values, percentages, fiscal periods, and arithmetic relations. This study formulates answer evaluation as continuous quality regression and binary adherence classification on the...

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Номзүйн дэлгэрэнгүй

Үндсэн зохиолч:	Lewis MacDonald
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Scitific Publication Center 2026-01-01
Цуврал:	Artificial Intelligence and Machine Learning Review
Нөхцлүүд:	retrieval-augmented generation financial question answering FinQA RAGBench answer-quality regression table-text evidence
Онлайн хандалт:	https://scipublication.com/index.php/AIMLR/article/view/418
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!