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Listening to Affected Communities to Define Extreme Speech: Dataset and Experiments ...
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Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization ...
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Graph Algorithms for Multiparallel Word Alignment
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ; The 2021 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-03424044 ; The 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Nov 2021, Punta Cana, Dominica ; https://2021.emnlp.org/ (2021)
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Does He Wink or Does He Nod? A Challenging Benchmark for Evaluating Word Understanding of Language Models ...
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Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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Discrete and Soft Prompting for Multilingual Models ...
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Abstract:
It has been shown for English that discrete and soft prompting perform strongly in few-shot learning with pretrained language models (PLMs). In this paper, we show that discrete and soft prompting perform better than finetuning in multilingual cases: Crosslingual transfer and in-language training of multilingual natural language inference. For example, with 48 English training examples, finetuning obtains 33.74% accuracy in crosslingual transfer, barely surpassing the majority baseline (33.33%). In contrast, discrete and soft prompting outperform finetuning, achieving 36.43% and 38.79%. We also demonstrate good performance of prompting with training data in multiple languages other than English. ... : EMNLP 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2109.03630 https://dx.doi.org/10.48550/arxiv.2109.03630
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ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus ...
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Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models ...
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Wine is Not v i n. -- On the Compatibility of Tokenizations Across Languages ...
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Locating Language-Specific Information in Contextualized Embeddings ...
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Measuring and Improving Consistency in Pretrained Language Models ...
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