4k citations · 13.4k across the 76 of their papers we have counts for
5 papers · 2 filters
Improving Neural Language Models with a Continuous Cache
Edouard Grave, Armand Joulin, Nicolas Usunier
We propose an extension to neural network language models to adapt their prediction to the recent history. Our model is a simplified version of memory augmented networks, which sto…
FastText.zip: Compressing text classification models
Armand Joulin, Edouard Grave, Piotr Bojanowski +3
We consider the problem of producing compact architectures for text classification, such that the full model fits in a limited amount of memory. After considering different solutio…
Efficient softmax approximation for GPUs
Edouard Grave, Armand Joulin, Moustapha Cissé +2
We propose an approximate strategy to efficiently train neural network based language models over very large vocabularies. Our approach, called adaptive softmax, circumvents the li…
Bag of Tricks for Efficient Text Classification
Armand Joulin, Edouard Grave, Piotr Bojanowski +1
This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifi…
Enriching Word Vectors with Subword Information
Piotr Bojanowski, Edouard Grave, Armand Joulin +1
Continuous word representations, trained on large unlabeled corpora are useful for many natural language processing tasks. Popular models that learn such representations ignore the…