373 citations · 419 across the 6 of their papers we have counts for
6 papers
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
Seamless Communication, Loïc Barrault, Yu-An Chung +65
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed…
xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages
Mingda Chen, Kevin Heffernan, Onur Çelebi +2
We introduce a new proxy score for evaluating bitext mining based on similarity in a multilingual embedding space: xSIM++. In comparison to xSIM, this improved proxy leverages rule…
Multilingual Representation Distillation with Contrastive Learning
Weiting Tan, Kevin Heffernan, Holger Schwenk +1
Multilingual sentence representations from large models encode semantic information from two or more languages and can be used for different cross-lingual information retrieval and…
No Language Left Behind: Scaling Human-Centered Machine Translation
NLLB Team, Marta R. Costa-jussà, James Cross +36
Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However,…
Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages
Kevin Heffernan, Onur Çelebi, Holger Schwenk
Scaling multilingual representation learning beyond the hundred most frequent languages is challenging, in particular to cover the long tail of low-resource languages. A promising…
Unsupervised Topic Segmentation of Meetings with BERT Embeddings
Alessandro Solbiati, Kevin Heffernan, Georgios Damaskinos +3
Topic segmentation of meetings is the task of dividing multi-person meeting transcripts into topic blocks. Supervised approaches to the problem have proven intractable due to the d…