5 citations · 5 across the 5 of their papers we have counts for
5 papers
On Measuring Context Utilization in Document-Level MT Systems
Wafaa Mohammed, Vlad Niculae
Document-level translation models are usually evaluated using general metrics such as BLEU, which are not informative about the benefits of context. Current work on context-aware e…
Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair Variables
Ali Araabi, Vlad Niculae, Christof Monz
Despite the tremendous success of Neural Machine Translation (NMT), its performance on low-resource language pairs still remains subpar, partly due to the limited ability to handle…
DAG Learning on the Permutahedron
Valentina Zantedeschi, Luca Franceschi, Jean Kaddour +2
We propose a continuous optimization framework for discovering a latent directed acyclic graph (DAG) from observational data. Our approach optimizes over the polytope of permutatio…
How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?
Ali Araabi, Christof Monz, Vlad Niculae
Neural Machine Translation (NMT) is an open vocabulary problem. As a result, dealing with the words not occurring during training (a.k.a. out-of-vocabulary (OOV) words) have long b…
Notes on Latent Structure Models and SPIGOT
André F. T. Martins, Vlad Niculae
These notes aim to shed light on the recently proposed structured projected intermediate gradient optimization technique (SPIGOT, Peng et al., 2018). SPIGOT is a variant of the str…