12 citations · 13 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Making Sentence Embeddings Robust to User-Generated Content
Lydia Nishimwe, Benoît Sagot, Rachel Bawden
NLP models have been known to perform poorly on user-generated content (UGC), mainly because it presents a lot of lexical variations and deviates from the standard texts on which m…
cs.CL2023★ 1 cited
Investigating Lexical Sharing in Multilingual Machine Translation for Indian Languages
Sonal Sannigrahi, Rachel Bawden
Multilingual language models have shown impressive cross-lingual transfer ability across a diverse set of languages and tasks. To improve the cross-lingual ability of these models,…
cs.CL2023★ 12 cited
Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM
Rachel Bawden, François Yvon
The NLP community recently saw the release of a new large open-access multilingual language model, BLOOM (BigScience et al., 2022) covering 46 languages. We focus on BLOOM's multil…