activity
20192022
most citedMultilingual is not enough: BERT for Finnish

120 citations · 212 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CL2022

Out-of-Domain Evaluation of Finnish Dependency Parsing

Jenna Kanerva, Filip Ginter

The prevailing practice in the academia is to evaluate the model performance on in-domain evaluation data typically set aside from the training corpus. However, in many real world…

cs.CL20213 cited

Annotation Guidelines for the Turku Paraphrase Corpus

Jenna Kanerva, Filip Ginter, Li-Hsin Chang +8

This document describes the annotation guidelines used to construct the Turku Paraphrase Corpus. These guidelines were developed together with the corpus annotation, revising and e…

cs.CL2021

Quantitative Evaluation of Alternative Translations in a Corpus of Highly Dissimilar Finnish Paraphrases

Li-Hsin Chang, Sampo Pyysalo, Jenna Kanerva +1

In this paper, we present a quantitative evaluation of differences between alternative translations in a large recently released Finnish paraphrase corpus focusing in particular on…

cs.CL20215 cited

Finnish Paraphrase Corpus

Jenna Kanerva, Filip Ginter, Li-Hsin Chang +7

In this paper, we introduce the first fully manually annotated paraphrase corpus for Finnish containing 53,572 paraphrase pairs harvested from alternative subtitles and news headin…

cs.CL2020

Towards Fully Bilingual Deep Language Modeling

Li-Hsin Chang, Sampo Pyysalo, Jenna Kanerva +1

Language models based on deep neural networks have facilitated great advances in natural language processing and understanding tasks in recent years. While models covering a large…

cs.CL202027 cited

WikiBERT models: deep transfer learning for many languages

Sampo Pyysalo, Jenna Kanerva, Antti Virtanen +1

Deep neural language models such as BERT have enabled substantial recent advances in many natural language processing tasks. Due to the effort and computational cost involved in th…