This paper presents DeepSPIN's submissions to Tasks 0 and 1 of the SIGMORPHON 2020 Shared Task. For both tasks, we present multilingual models, training jointly ...
For both tasks, we present multilingual models, training jointly on data in all languages. We perform no language- specific hyperparameter tuning – each of our.
This paper presents DeepSPIN's submissions to Tasks 0 and 1 of the SIGMORPHON 2020 Shared Task, and presents multilingual models, training jointly on data ...
This paper presents DeepSPIN's submissions to Tasks 0 and 1 of the SIGMORPHON 2020 Shared Task. For both tasks, we present multilingual models, ...
We sample data from MIGHTYMORPH for 3 clause-level morphological tasks: inflection, reinflection, and analysis. We experiment with standard and ...
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For both tasks, we present multilingual models, training jointly on data in all languages. We perform no language-specific hyperparameter tuning – each of our ...
Jul 9, 2023 · • No one-size-fits-all multilingual prompting strategy. • Challenge ... Fine-tuned models for the most part outperform prompting LLMs on ...
Oct 12, 2020 · In this paper, we propose to generate smaller models that handle fewer number of languages according to the targeted corpora.
Jul 18, 2019 · Multilingual NMT systems differ from other state-of-the-art systems in that they use one model for all languages, rather than one model per ...
Oct 24, 2022 · Translate-train-all: a single multilingual model is fine-tuned on the machine-translated version of the training set in all different languages, ...