UA4RAG (UnAnswerable for RAG) is a collection of datasets designed to train and evaluate language models on generating and recognizing unanswerable factual questions and appropriate non-answers given a reference text.
In retrieval-augmented generation (RAG) systems, retrieved contexts are often tangential to user queries. This dataset addresses the critical challenge of training models to recognize when sufficient evidence is absent and to… See the full description on the dataset page:
https://huggingface.co/datasets/lopozz/UA4RAG-it.
