34 datasets found

WikiText-103 and Enwik8 datasets are used for language modeling tasks

The dataset used in the paper is the Wikipedia2Vec dataset, which contains word embeddings.

The authors used the CHILDES corpus to train a character-based LSTM model and evaluated its performance on a set of tasks.

The Character Level Penn Treebank dataset is a benchmark for evaluating the ability of RNNs to model language.

The Pile dataset contains 3.5 million samples of diverse text for language modeling.

Large-scale dataset of L1 and L2 scripted and spontaneous transcripts and recordings

The Enwik8 dataset is a large-scale language modeling dataset.

Highly regularized LSTMs achieve impressive results on several benchmark datasets in language modeling. We propose a new regularization method based on decoding the last token...

Enhancing the TED-LIUM corpus with selected data for language modeling and more TED talks.

The One Billion Word dataset is a large dataset of text, containing 0.8 billion words belonging to a vocabulary of 793 471 words. The dataset is used for word-level language...

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...

Penn Treebank PCFG dataset

Simple CFG dataset

The Semantic Attribute Modulation (SAM) for language modeling and style variation.

The Penn Tree Bank (PTB) dataset used for language modeling.

The dataset used for language modeling, disentangled representation learning, and image generation.

The dataset used in the paper is the bookcorpus dataset.

Bilingual word embeddings from parallel and non-parallel corpora for cross-language text classification

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.

The dataset contains 768M tokens for language modeling.