RetrievalQA is a short-form open-domain question answering (QA) dataset consisting of 1,271 questions covering new world and long-tail knowledge.
We ensure the knowledge necessary to answer the questions is absent from most LLMs. Therefore, LLMs must truthfully decide whether to retrieve to be able to answer the questions correctly.
RetrievalQA enables us to evaluate the effectiveness of adaptive retrieval-augmented generation (RAG) approaches, an aspect… See the full description on the dataset page:
https://huggingface.co/datasets/zihanz/RetrievalQA.
