12 datasets found

The dataset used in the paper is the Stanford Sentiment Treebank (SST) dataset, which contains standard train/dev/test sets and two subtasks: binary sentence classification or...

Sentiment training dataset for LABDet, a robust and language-agnostic bias probing method to quantify intrinsic bias in monolingual PLMs.

A dataset for sentiment analysis on German reviews.

A dataset for sentiment analysis on English reviews.

A dataset for sentiment analysis on Spanish reviews.

A novel model for universal and unsupervised sentiment analysis driven by a set of syntactic rules for semantic composition.

The dataset used for the experiments across ten models– ranging from bag-of-words models to pre-trained transformers– and find that a model having higher AUC does not necessarily...

The dataset used in the paper is a language domain dataset, specifically for sentiment classification, named AG News. The dataset is used to evaluate the performance of...

The dataset used in the paper is the Stanford Natural Language Inference (SNLI) dataset, which consists of 549,367 premise-hypothesis pairs for train/dev/test sets and target...

The dataset used for sentiment analysis, question type classification, and subjectivity classification tasks.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors tested the proposed method on three real data sets for the most relevant security...

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...