In Retrieval-Augmented Generation (RAG), ensuring accuracy and reliability is essential. RAGognize is a dataset created to help researchers and developers study and improve how AI systems use retrieved information. By offering structured examples and natural token-level closed-domain hallucination annotations, it provides a resource for analyzing model behavior and developing methods that… See the full description on the dataset page: https://huggingface.co/datasets/F4biian/RAGognize-with-samples-test.
