activity
20192022
most citedHow multilingual is Multilingual BERT?

140 citations · 191 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL20222 cited

Dialect-robust Evaluation of Generated Text

Jiao Sun, Thibault Sellam, Elizabeth Clark +6

Evaluation metrics that are not robust to dialect variation make it impossible to tell how well systems perform for many groups of users, and can even penalize systems for producin…

cs.CL20221 cited

Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks

Rochelle Choenni, Dan Garrette, Ekaterina Shutova

Large multilingual language models typically share their parameters across all languages, which enables cross-lingual task transfer, but learning can also be hindered when training…

cs.CL2021

Frequency Effects on Syntactic Rule Learning in Transformers

Jason Wei, Dan Garrette, Tal Linzen +1

Pre-trained language models perform well on a variety of linguistic tasks that require symbolic reasoning, raising the question of whether such models implicitly represent abstract…

cs.CL2020

Improving Multilingual Models with Language-Clustered Vocabularies

Hyung Won Chung, Dan Garrette, Kiat Chuan Tan +1

State-of-the-art multilingual models depend on vocabularies that cover all of the languages the model will expect to see at inference time, but the standard methods for generating…

cs.CL2020

TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages

Jonathan H. Clark, Eunsol Choi, Michael Collins +4

Confidently making progress on multilingual modeling requires challenging, trustworthy evaluations. We present TyDi QA---a question answering dataset covering 11 typologically dive…

cs.CL2019140 cited

How multilingual is Multilingual BERT?

Telmo Pires, Eva Schlinger, Dan Garrette

In this paper, we show that Multilingual BERT (M-BERT), released by Devlin et al. (2018) as a single language model pre-trained from monolingual corpora in 104 languages, is surpri…