12 citations · 46 across the 25 of their papers we have counts for
6 papers · 1 filter
Speeding Up Entmax
Maxat Tezekbayev, Vassilina Nikoulina, Matthias Gallé +1
Softmax is the de facto standard in modern neural networks for language processing when it comes to normalizing logits. However, by producing a dense probability distribution each…
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters
Asa Cooper Stickland, Alexandre Bérard, Vassilina Nikoulina
Adapter layers are lightweight, learnable units inserted between transformer layers. Recent work explores using such layers for neural machine translation (NMT), to adapt pre-train…
Efficient Inference for Multilingual Neural Machine Translation
Alexandre Berard, Dain Lee, Stéphane Clinchant +2
Multilingual NMT has become an attractive solution for MT deployment in production. But to match bilingual quality, it comes at the cost of larger and slower models. In this work,…
On the Evaluation of Machine Translation for Terminology Consistency
Md Mahfuz ibn Alam, Antonios Anastasopoulos, Laurent Besacier +4
As neural machine translation (NMT) systems become an important part of professional translator pipelines, a growing body of work focuses on combining NMT with terminologies. In ma…
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?
Zae Myung Kim, Laurent Besacier, Vassilina Nikoulina +1
Recent studies on the analysis of the multilingual representations focus on identifying whether there is an emergence of language-independent representations, or whether a multilin…
The Rediscovery Hypothesis: Language Models Need to Meet Linguistics
Vassilina Nikoulina, Maxat Tezekbayev, Nuradil Kozhakhmet +3
There is an ongoing debate in the NLP community whether modern language models contain linguistic knowledge, recovered through so-called probes. In this paper, we study whether lin…