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Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas ...
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AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages ...
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SemEval-2021 Task 12: Learning with Disagreements
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Abstract:
Disagreement between coders is ubiquitous in virtually all datasets annotated with human judgements in both natural language processing and computer vision. However, most supervised machine learning methods assume that a single preferred interpretation exists for each item, which is at best an idealization. The aim of the SemEval-2021 shared task on learning with disagreements (Le-Wi-Di) was to provide a unified testing framework for methods for learning from data containing multiple and possibly contradictory annotations covering the best-known datasets containing information about disagreements for interpreting language and classifying images. In this paper we describe the shared task and its results.
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URL: http://repository.essex.ac.uk/31851/1/2021.semeval-1.41.pdf http://repository.essex.ac.uk/31851/ https://doi.org/10.18653/v1/2021.semeval-1.41
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IAPUCP at SemEval-2021 task 1: Stacking fine-tuned transformers is almost all you need for lexical complexity prediction
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Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas
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In: Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas. Edited by: Mager, Manuel; Oncevay, Arturo; Rios, Annette; Meza Ruiz, Ivan Vladimir; Palmer, Alexis; Neubig, Graham; Kann, Katharina (2021). Online: Association for Computational Linguistics. (2021)
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It's not a Non-Issue: Negation as a Source of Error in Machine Translation ...
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A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ...
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SemEval-2020 Task 2: Predicting multilingual and cross-lingual (graded) lexical entailment
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Temporally-oriented possession: A corpus for tracking possession over time
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In: Proceedings of the Society for Computation in Linguistics (2019)
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A Man Needs a Female like a Fish Needs a Lobotomy: The Role of Adjectival Nominalization in Pejorative Meaning
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Discussions about documenting and archiving languages
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In: 2018 CoRSAL Symposium on Developing Infrastructure for a Computational Resource on South Asian Languages, November 1, 2018. Denton, TX. (2018)
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Speeches on language resources for endangered languages
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In: 2018 CoRSAL Symposium on Developing Infrastructure for a Computational Resource on South Asian Languages, November 1, 2018. Denton, TX. (2018)
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Illegal is not a Noun: Linguistic Form for Detection of Pejorative Nominalizations
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In: The First Workshop on Abusive Language Online, July 30-August 4, 2017. Vancouver, Canada. (2017)
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Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention
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In: 6th Joint Conference on Lexical and Computational Semantics, August 3-4, 2017. Vancouver, Canada. (2017)
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Photograph of a CoRSAL presentation
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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Photograph of a CoRSAL presentation
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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Speech on harmonized annotation and data
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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A View from CL/NLP
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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Harmonized Annotation and Data Formats
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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Speech about data structures needed for computational linguistics and NLP
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In: Developing Infrastructure for Computational Resources on South Asian Languages, November 17, 2017. Denton, TX. (2017)
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