420 datasets found

The WikiText-2 dataset is a benchmark for evaluating the performance of large language models.

The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors trained a GPT2 transformer language model on the C4 dataset.

Large Language Models (LLMs) have greatly advanced the natural language processing paradigm. However, the high computational load and huge model sizes pose a grand challenge for...

Automated discovery of mathematical definitions in text.

MathGloss is a project to create a knowledge graph (KG) for undergraduate mathematics from text, automatically, using modern natural language processing (NLP) tools and...

DEERLET is a dataset containing 846 tuples with format (fact, rule, label0, label1, label2, label3) for the task of classifying the capabilities required by inductive reasoning.

DEER is a dataset containing 1.2k rule-fact pairs for the task of inducing natural language rules from natural language facts.

Inductive reasoning is a core component of human intelligence. In the past research of inductive reasoning within computer science, logic language is used as representations of...

The CoNLL-2016 Shared Task (CoNLL16) provides more abundant annotation for shadow discourse parsing.

The Penn Discourse Treebank 2.0 (PDTB 2.0) is a large scale corpus containing 2,312 Wall Street Journal (WSJ) articles.

Implicit Discourse Relation Recognition (IDRR), which infers discourse relations without the help of explicit connectives, is still a crucial and challenging task for discourse...

The Banking77 dataset is a specialized dataset for intent classification in the banking domain.

The QQP dataset contains more than 400k question pairs.

The Penn Tree Bank dataset is a corpus split into a training, validation and testing set of 929k words, a validation set of 73k words, and a test set of 82k words. The...

A self-recognition test for language models using model-generated security questions.

The dataset used in this study to analyze the self-assessment behavior of Large language models.

The Xl-sum dataset for multilingual abstractive summarization

The Cross-Lingual Ability of Multilingual BERT dataset

The dataset used in this paper for multilingual language models

The dataset used in the paper is a collection of sentence classification tasks, including SST-2, SNLI, and PubMed.