In Africa, and the world at large, there is an increasing focus on devel...
In this work, we develop and release Llama 2, a collection of pretrained...
Machine Translation (MT) has been widely used for cross-lingual
classifi...
Existing metrics for evaluating the quality of automatically generated
q...
Driven by the goal of eradicating language barriers on a global scale,
m...
Generating factual, long-form text such as Wikipedia articles raises thr...
Users and organizations are generating ever-increasing amounts of privat...
Multi-task learning with an unbalanced data distribution skews model lea...
Recent work in multilingual machine translation (MMT) has focused on the...
We describe Facebook's multilingual model submission to the WMT2021 shar...
One of the biggest challenges hindering progress in low-resource and
mul...
Attention mechanisms have shown promising results in sequence modeling t...
Pretrained multilingual models are able to perform cross-lingual transfe...
Semantic parsing using sequence-to-sequence models allows parsing of dee...
The two main research threads in computer-based music generation are: th...
While research on explaining predictions of open-domain QA systems (ODQA...
This paper describes Facebook AI's submission to WMT20 shared news
trans...
Fact checking at scale is difficult – while the number of active fact
ch...
Generating text from structured data is challenging because it requires
...
Existing work in translation demonstrated the potential of massively
mul...
We introduce k-nearest-neighbor machine translation (kNN-MT), which
pred...
Challenging problems such as open-domain question answering, fact checki...
Recent work demonstrates the potential of multilingual pretraining of
cr...
We present our view of what is necessary to build an engaging open-domai...
Machine learning models are trained to find patterns in data. NLP models...
Progress in Sentence Simplification has been hindered by the lack of
sup...
Various machine learning tasks can benefit from access to external
infor...
We tackle the problem of producing compact models, maximizing their accu...
We tackle the problem of producing compact models, maximizing their accu...
Transformers are feedforward networks that can process input tokens in
p...
Procedurally generating cohesive and interesting game environments is
ch...
Models often easily learn biases present in the training data, and their...
Query-based open-domain NLP tasks require information synthesis from lon...
Overparameterized transformer networks have obtained state of the art re...
We introduce the first large-scale corpus for long-form question answeri...
We propose a method to learn unsupervised sentence representations in a
...
fairseq is an open-source sequence modeling toolkit that allows research...
We introduce a large scale crowdsourced text adventure game as a researc...
Writers generally rely on plans or sketches to write long stories, but m...
Self-attention is a useful mechanism to build generative models for lang...
In open-domain dialogue intelligent agents should exhibit the use of
kno...
We explore story generation: creative systems that can build coherent an...
Current models for document summarization ignore user preferences such a...
Latent Dirichlet Allocation (LDA) models trained without stopword remova...
The pre-dominant approach to language modeling to date is based on recur...