182 datasets found

The Clickbait Challenge 2017 dataset, a collection of social media posts and their corresponding article titles, used for clickbait detection.

The dataset used for testing the sLDA model [16].

The FNC-1 dataset is a supervised classification task for stance detection, where the goal is to automatically predict the labels in a supervised classification task.

The dataset used in this study for image and text classification tasks.

The dataset used in this paper is not explicitly described, but it is mentioned that it is a large language model (LLM) and that the authors used it to train and evaluate their...

The dataset used in the paper is the Multitask Language Understanding (MMLU) dataset, which consists of 57 tasks from Science, Technology, Engineering, and Math (STEM),...

The dataset is used for multilabel learning tasks. It contains 7395 documents, each labeled with 159 relevant tickers.

Text categorization, a document may be associated with a range of topics, such as science, entertainment, and news.

The dataset used in this paper is SST-2, Irony, IronyB, TREC6, and SNIPS.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a variety of datasets for semi-supervised learning tasks.

Two datasets used for multi-task learning, CIFAR-100 and AGNews.

The dataset used in the paper is a large-scale corpus of movie reviews from the Socher et al. (2013) dataset.

Cross-topic Argument Mining from Heterogeneous Sources.

Semeval-2016 Task 6: Detecting stance in tweets.

Stance detection aims to identify whether the author of a text is in favor of, against, or neutral to a given target. The main challenge of this task comes two-fold: few-shot...

The dataset is a combination of 3 singular datasets: A Million News Headlines, Fake and real news, Getting Real about Fake News.

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

The dataset used for toxicity and stereotype mitigation task, which consists of 25 thousand examples of positive and negative movie reviews.

The dataset used in the paper is a concatenation of the original Harry Potter books and synthetic discussions, blog posts, and wiki-like entries about the books.

The dataset used in the paper is the Equity Evaluation Corpus (EEC) for emotion prediction, which contains a balanced dataset of sentences with emotions.