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Morphological Processing of Low-Resource Languages: Where We Are and What's Next ...
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Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability ...
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Don't Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data ...
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Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages ...
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How to Adapt Your Pretrained Multilingual Model to 1600 Languages ...
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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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{PROST}: {P}hysical Reasoning about Objects through Space and Time ...
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Don't Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data ...
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How to Adapt Your Pretrained Multilingual Model to 1600 Languages ...
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AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages ...
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CLiMP: A Benchmark for Chinese Language Model Evaluation ...
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Learning to Learn Morphological Inflection for Resource-Poor Languages ...
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16 |
Acquisition of Inflectional Morphology in Artificial Neural Networks With Prior Knowledge
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In: Proceedings of the Society for Computation in Linguistics (2020)
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Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings
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Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings ...
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20 |
Acquisition of Inflectional Morphology in Artificial Neural Networks With Prior Knowledge ...
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