2023
ACL
ACL 2023
SIGMORPHON–UniMorph 2023 Shared Task 0: Typologically Diverse Morphological Inflection
Abstract
AbstractThe 2023 SIGMORPHON–UniMorph shared task on typologically diverse morphological inflection included a wide range of languages: 26 languages from 9 primary language families. The data this year was all lemma-split, to allow testing models’ generalization ability, and structured along the new hierarchical schema presented in (Batsuren et al., 2022). The systems submitted this year, 9 in number, showed ingenuity and innovativeness, including hard attention for explainability and bidirectional decoding. Special treatment was also given by many participants to the newly-introduced data in Japanese, due to the high abundance of unseen Kanji characters in its test set.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— typologically diverse language
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Learning Types > Zero-Shot Learning
Interdisciplinary > Linguistics > Computational Linguistics
Interdisciplinary > Linguistics > Morphology
Machine Learning > Learning Types > Transfer Learning
Natural Language Processing > Understanding > Morphology
Machine Learning > Learning Types > Multi-Label Learning