activity
20172022
most citedConfidence through Attention

20 citations · 28 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CL20221 cited

Cross-lingual Similarity of Multilingual Representations Revisited

Maksym Del, Mark Fishel

Related works used indexes like CKA and variants of CCA to measure the similarity of cross-lingual representations in multilingual language models. In this paper, we argue that ass…

cs.CL20215 cited

Translation Transformers Rediscover Inherent Data Domains

Maksym Del, Elizaveta Korotkova, Mark Fishel

Many works proposed methods to improve the performance of Neural Machine Translation (NMT) models in a domain/multi-domain adaptation scenario. However, an understanding of how NMT…

cs.CL20212 cited

Extremely low-resource machine translation for closely related languages

Maali Tars, Andre Tättar, Mark Fišel

An effective method to improve extremely low-resource neural machine translation is multilingual training, which can be improved by leveraging monolingual data to create synthetic…

cs.CL2020

Unsupervised Quality Estimation for Neural Machine Translation

Marina Fomicheva, Shuo Sun, Lisa Yankovskaya +6

Quality Estimation (QE) is an important component in making Machine Translation (MT) useful in real-world applications, as it is aimed to inform the user on the quality of the MT o…

cs.CL2019

Grammatical Error Correction and Style Transfer via Zero-shot Monolingual Translation

Elizaveta Korotkova, Agnes Luhtaru, Maksym Del +3

Both grammatical error correction and text style transfer can be viewed as monolingual sequence-to-sequence transformation tasks, but the scarcity of directly annotated data for ei…

cs.CL2018

Monolingual and Cross-lingual Zero-shot Style Transfer

Elizaveta Korotkova, Maksym Del, Mark Fishel

We introduce the task of zero-shot style transfer between different languages. Our training data includes multilingual parallel corpora, but does not contain any parallel sentences…