5 citations · 6 across the 3 of their papers we have counts for
5 papers
BPE Gets Picky: Efficient Vocabulary Refinement During Tokenizer Training
Pavel Chizhov, Catherine Arnett, Elizaveta Korotkova +1
Language models can largely benefit from efficient tokenization. However, they still mostly utilize the classical BPE algorithm, a simple and reliable method. This has been shown t…
Beyond Toxic: Toxicity Detection Datasets are Not Enough for Brand Safety
Elizaveta Korotkova, Isaac Chung
The rapid growth in user generated content on social media has resulted in a significant rise in demand for automated content moderation. Various methods and frameworks have been p…
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…
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…
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…