103 datasets found

Stance detection dataset for political stance detection, including P-Stance, SemEval-2016, and MTSD datasets.

The UNIREX framework extends the approach to a more general setting.

The Movie Reviews dataset contains positive and negative movie reviews with rationales annotated by humans to support classification.

The DBpedia Animals dataset comprises 10,000 English Wikipedia article abstracts for animal species.

The DynaSent dataset contains approximately 122,000 sentences, each labeled as positive, neutral, or negative.

Rcv1: A new benchmark collection for text categorization research.

AGNews, 20News, NYT, IMDB are datasets used for weakly supervised text classification.

The HateXplain dataset, containing 20,000 posts from Gab and Twitter, annotated with hate/offensive/normal labels.

CLIMABENCH is a benchmark of climate-related text classification tasks. It collates five existing climate change-related text datasets, including CLIMATEXT, CLIMATESTANCE,...

The dataset used in this paper is a collection of news articles from AllNews.

The dataset used in this paper is a collection of documents from Wikipedia.

The NeurIPS dataset is a collection of 7241 papers published in NeurIPS from 1987 to 2016.

The dataset used in the paper is the Wikipedia dataset, which contains over six million English Wikipedia articles with a full-text field associated with 50 training queries...

Topic modeling has been a widely used tool for unsupervised text analysis. However, comprehensive evaluations of a topic model remain challenging.

The Reuters dataset is a text classification dataset containing 21,578 samples.

The dataset used in the paper is a collection of adversarial examples and natural examples for text classification tasks.

Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices...

Text dataset for text classification and sentiment analysis tasks.

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

The problem of similarity search is to find the most similar items in a large collection to a query item of interest. Fast similarity search is at the core of many information...