8 datasets found

Open-domain question answering (OpenQA) aims to seek answers for a broad range of questions from a large knowledge source, e.g., structured knowledge bases and unstructured...

A unified system to answer open-domain questions that may require a varying number of retrieval steps.

Visual question answering (VQA) demands simultaneous comprehension of both the image visual content and natural language questions. In some cases, the reasoning needs the help...

The dataset used in the paper for negative augmentation with language model for reading comprehension of abstract meaning

DROP dataset contains complex compositional questions against natural language passages describing football games and historical events.

The dataset used in the paper is a multiple-choice reading comprehension dataset, which includes a passage, question, and answer. The passage is a script, and the question is a...

The TriviaQA dataset is a collection of questions sourced from Quiz League websites, with sentence-level supporting facts annotation.

The SQuAD 2.0 dataset is a new challenging task for natural language processing, which requires that machine can read, understand, and answer questions about a text. The dataset...