FinDER is a benchmark dataset designed for evaluating Retrieval-Augmented Generation (RAG) in financial question answering. It consists of 5,703 expert-annotated query–evidence–answer triplets derived from real-world 10-K filings and ambiguous financial queries submitted by industry professionals.
This dataset captures the domain-specific challenges of financial QA, including short… See the full description on the dataset page:
https://huggingface.co/datasets/Linq-AI-Research/FinDER.
