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Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words.

, , and . ACL/IJCNLP (1), page 3594-3608. Association for Computational Linguistics, (2021)

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Geographic Adaptation of Pretrained Language Models., , , , and . CoRR, (2022)Modeling Ideological Agenda Setting and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity., , and . CoRR, (2021)Paloma: A Benchmark for Evaluating Language Model Fit., , , , , , , , , and 6 other author(s). CoRR, (2023)The better your Syntax, the better your Semantics? Probing Pretrained Language Models for the English Comparative Correlative., , , and . EMNLP, page 10859-10882. Association for Computational Linguistics, (2022)Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words., , and . ACL/IJCNLP (1), page 3594-3608. Association for Computational Linguistics, (2021)A Graph Auto-encoder Model of Derivational Morphology., , and . ACL, page 1127-1138. Association for Computational Linguistics, (2020)Predicting the Growth of Morphological Families from Social and Linguistic Factors., , and . ACL, page 7273-7283. Association for Computational Linguistics, (2020)Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models., , , , , , and . CoRR, (2024)Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research., , , , , , , , , and 26 other author(s). CoRR, (2024)An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model Tokenizers., , and . ACL (2), page 385-393. Association for Computational Linguistics, (2022)