39 datasets found

The Aggrefact-Unified dataset is a collection of news documents and summaries with factual errors.

IgboSum1500 is an Igbo text summarization dataset, housing 1,500 articles.

The Rotten Tomatoes dataset has 5331 positive and 5331 negative review sentences.

The dataset used in this paper for sentence reduction task.

The authors used the TL;DR dataset, which consists of reddit posts with summaries.

The Famous Keyword Twitter Replies dataset is a comprehensive collection of Twitter data that focuses on popular keywords and their associated replies.

The dataset used in the paper is a document summarization dataset. The goal is to extract sentences (with character budget B) to maximize coverage of human-annotated summaries.

The dataset used for the text summarization task, where a summarizer produces an utterance made up of one or multiple sentences to succinctly report the main content of a text.

The paper proposes a novel approach to the sequential example selection paradigm for in-context learning.

Wikipedia Current Events Portal (WCEP) dataset, which consists of short, human-written summaries of news events, the articles for which are all extracted from the Wikipedia...

The dataset used in the paper is a collection of 45K news articles and corresponding summaries, where each summary is professionally crafted and provides links to the original...

Two multi-document summarization datasets from the Text Analysis Conference (TAC) shared tasks: TAC’08 and TAC’09.

The XSUM dataset comprises 226,711 British Broadcasting Corporation (BBC) articles paired with their single-sentence summaries.

Multi-document summarization datasets

Text summarization and data-to-text generation datasets

Text summarization and data-to-text generation datasets

The NewsRoom dataset consists of 60 input source texts and 7 output summaries for each sample.

DUC-2004 dataset is used for sentence summarization. It contains 500 documents, each with 4 model summaries.

The TEDLIUM corpus is a large-volume corpus used for speech recognition and text summarization.

Text summarization aims to extract essential information from a piece of text and transform the text into a concise version.