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Applying the Transformer to Character-level Transduction ...
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Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction ...
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Applying the Transformer to Character-level Transduction
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In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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Do Explicit Alignments Robustly Improve Multilingual Encoders? ...
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SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth; Mielke, Sabrina J.; Wu, Shijie; Ponti, Edoardo; Maudslay, Rowan Hall; Zmigrod, Ran; Valvoda, Josef; Toldova, Svetlana; Tyers, Francis; Klyachko, Elena; Yegorov, Ilya; Krizhanovsky, Natalia; Czarnowska, Paula; Nikkarinen, Irene; Krizhanovsky, Andrew; Pimentel, Tiago; Hennigen, Lucas Torroba; Kirov, Christo; Nicolai, Garrett; Williams, Adina; Anastasopoulos, Antonios; Cruz, Hilaria; Chodroff, Eleanor; Cotterell, Ryan; Silfverberg, Miikka; Hulden, Mans. - : arXiv, 2020
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Abstract:
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from just one language such as English. The SIGMORPHON 2020 shared task on morphological reinflection aims to investigate systems' ability to generalize across typologically distinct languages, many of which are low resource. Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages. A total of 22 systems (19 neural) from 10 teams were submitted to the task. All four winning systems were neural (two monolingual transformers and two massively multilingual RNN-based models with gated attention). Most teams demonstrate utility of data hallucination and augmentation, ensembles, and multilingual training for low-resource languages. Non-neural learners and manually designed grammars showed ... : 39 pages, SIGMORPHON ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2006.11572 https://arxiv.org/abs/2006.11572
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The Paradigm Discovery Problem
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In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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Emerging Cross-lingual Structure in Pretrained Language Models ...
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The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ...
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