24 datasets found

The dataset used in this paper is the WebText dataset, which is a widely used dataset for natural language processing tasks.

MTG is a multilingual multiway text generation benchmark suite. It is the first-proposed multilingual multiway text generation dataset with the largest human-annotated data...

A dataset for automatically generating macro research reports from economic news.

The M4 dataset consists of human-written texts from several data sources, including Wikipedia, Reddit, and arXiv in the English subset of the dataset. It pairs the human-written...

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

The BOLD dataset contains professional prompts for text generation, focusing on gender equality.

The dataset used in this paper for text generation with attribute controls.

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

A large native one-to-many text dataset for text generation tasks, constructed to accelerate the research of diverse text generation.

This dataset is used to test the ability of large language models to detect and correct biased Wikipedia edits according to Wikipedia's Neutral Point of View (NPOV) policy.

A corpus and cloze evaluation for deeper understanding of commonsense stories.

The ROCStories corpus is a collection of crowdsourced five-sentence everyday stories rich in causal and temporal relations.

A corpus and cloze evaluation for deeper understanding of commonsense stories.

The E2E dataset contains restaurant reviews labeled by 8 fields including food type, price, and customer rating.

Persona-Chat is sourced from authentic conversations between human annotators who are randomly matched and assigned persona information.

The dataset used for the text-to-image task consists of 20 context tokens, to which three fixed tokens have been concatenated, representing the static context "the picture of".

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used the Wikitext-2 dataset for text generation tasks.

Commonsense generation aims to generate a realistic sentence describing a daily scene under the given concepts, which is very challenging, since it requires models to have...

Wizard of Wikipedia is a recent, large-scale dataset of multi-turn knowledge-grounded dialogues between a “apprentice” and a “wizard”, who has access to information from...

Word2Vec is a distributed word embedding generator that uses an artificial neural network to learn dense vector representations of words.