Papers by Stephane Clinchant
Efficient Inference for Multilingual Neural Machine Translation (2021.emnlp-main)
Copied to clipboard
| Challenge: | Multilingual NMT is an attractive solution for production, but to match bilingual quality, it comes at the cost of larger and slower models. |
| Approach: | They propose to use a shallow decoder with vocabulary filtering to speed up inference . they validate their findings with BLEU and chrF on 380 language pairs . |
| Outcome: | The proposed approach can be used in two 20-language multi-parallel settings. |
On the use of BERT for Neural Machine Translation (D19-56)
Copied to clipboard
| Challenge: | Existing studies on using pretrained language models for supervised NMT have not been successful. |
| Approach: | They propose to integrate BERT pretrained models with supervised NMT models by using monolingual data. |
| Outcome: | The proposed models improve translation quality in English-German, English-Russian and IWSLT14 datasets. |