326 citations · 514 across the 6 of their papers we have counts for
7 papers
MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation
Anna Currey, Maria Nădejde, Raghavendra Pappagari +5
As generic machine translation (MT) quality has improved, the need for targeted benchmarks that explore fine-grained aspects of quality has increased. In particular, gender accurac…
A baseline revisited: Pushing the limits of multi-segment models for context-aware translation
Suvodeep Majumder, Stanislas Lauly, Maria Nadejde +2
This paper addresses the task of contextual translation using multi-segment models. Specifically we show that increasing model capacity further pushes the limits of this approach a…
Joint translation and unit conversion for end-to-end localization
Georgiana Dinu, Prashant Mathur, Marcello Federico +2
A variety of natural language tasks require processing of textual data which contains a mix of natural language and formal languages such as mathematical expressions. In this paper…
Does Neural Machine Translation Benefit from Larger Context?
Sebastien Jean, Stanislas Lauly, Orhan Firat +1
We propose a neural machine translation architecture that models the surrounding text in addition to the source sentence. These models lead to better performance, both in terms of…
Document Neural Autoregressive Distribution Estimation
Stanislas Lauly, Yin Zheng, Alexandre Allauzen +1
We present an approach based on feed-forward neural networks for learning the distribution of textual documents. This approach is inspired by the Neural Autoregressive Distribution…
An Autoencoder Approach to Learning Bilingual Word Representations
Sarath Chandar A P, Stanislas Lauly, Hugo Larochelle +4
Cross-language learning allows us to use training data from one language to build models for a different language. Many approaches to bilingual learning require that we have word-l…
Learning Multilingual Word Representations using a Bag-of-Words Autoencoder
Stanislas Lauly, Alex Boulanger, Hugo Larochelle
Recent work on learning multilingual word representations usually relies on the use of word-level alignements (e.g. infered with the help of GIZA++) between translated sentences, i…