8 citations · 15 across the 7 of their papers we have counts for
7 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification
Konstantin Chernyshev, Ekaterina Garanina, Duygu Bayram +2
Misogyny and sexism are growing problems in social media. Advances have been made in online sexism detection but the systems are often uninterpretable. SemEval-2023 Task 10 on Expl…
Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine Translation
Lukas Edman, Gabriele Sarti, Antonio Toral +2
Pretrained character-level and byte-level language models have been shown to be competitive with popular subword models across a range of Natural Language Processing (NLP) tasks. H…
Subword-Delimited Downsampling for Better Character-Level Translation
Lukas Edman, Antonio Toral, Gertjan van Noord
Subword-level models have been the dominant paradigm in NLP. However, character-level models have the benefit of seeing each character individually, providing the model with more d…
Patching Leaks in the Charformer for Efficient Character-Level Generation
Lukas Edman, Antonio Toral, Gertjan van Noord
Character-based representations have important advantages over subword-based ones for morphologically rich languages. They come with increased robustness to noisy input and do not…
The Importance of Context in Very Low Resource Language Modeling
Lukas Edman, Antonio Toral, Gertjan van Noord
This paper investigates very low resource language model pretraining, when less than 100 thousand sentences are available. We find that, in very low resource scenarios, statistical…
Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language
Lukas Edman, Ahmet Üstün, Antonio Toral +1
This paper describes the methods behind the systems submitted by the University of Groningen for the WMT 2021 Unsupervised Machine Translation task for German--Lower Sorbian (DE--D…