12 datasets found

The dataset for the task of identifying if a desire expressed by a subject in a given short piece of text was fulfilled.

The SQuAD dataset is a benchmark for natural language understanding tasks, including question answering and text classification.

The MASSIVE dataset is a comprehensive collection of approximately one million annotated utterances for various natural language understanding tasks such as slot-filling, intent...

TreeMix is a compositional data augmentation approach for natural language understanding. It leverages constituency parsing tree to decompose sentences into sub-structures and...

The CoQA dataset is a benchmark for question answering research. It consists of conversational questions.

The Natural Instructions (NI) dataset used for evaluating the performance of the DEPTH model on natural language understanding tasks.

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 Natural Questions dataset consists of questions extracted from web queries, with each question accompanied by a corresponding Wikipedia article containing the answer.

The Bing dataset is a large-scale dataset for natural language understanding and question answering.

The MS MARCO dataset is a large-scale dataset for natural language understanding and question answering.

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...

Pre-trained language models (PrLM) have to carefully manage input units when training on a very large text with a vocabulary consisting of millions of words. Previous works have...