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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 When classifying grammatical role, BERT doesn't care about word order... except when it matters ... Papadimitriou, Isabel; Futrell, Richard; Mahowald, Kyle. - : arXiv, 2022 BASE Show details 2 Grammatical cues are largely, but not completely, redundant with word meanings in natural language ... Mahowald, Kyle; Diachek, Evgeniia; Gibson, Edward. - : arXiv, 2022 BASE Show details 3 Decrypting Cryptic Crosswords: Semantically Complex Wordplay Puzzles as a Target for NLP ... Rozner, Joshua; Potts, Christopher; Mahowald, Kyle. - : arXiv, 2021 BASE Show details 4 A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space ... Jones, Alex; Wang, William Yang; Mahowald, Kyle. - : arXiv, 2021 BASE Show details 5 Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT ... Papadimitriou, Isabel; Chi, Ethan A.; Futrell, Richard. - : arXiv, 2021 BASE Show details 6 Decrypting cryptic crosswords: Semantically complex wordplay puzzles as a target for NLP ... Rozner, Joshua; Potts, Christopher; Mahowald, Kyle. - : Dryad, 2021 Abstract: Cryptic crosswords, the dominant crossword variety in the UK, are a promising target for advancing NLP systems that seek to process semantically complex, highly compositional language. Cryptic clues read like fluent natural language but are adversarially composed of two parts: a definition and a wordplay cipher requiring character-level manipulations. Expert humans use creative intelligence to solve cryptics, flexibly combining linguistic, world, and domain knowledge. In this paper, we make two main contributions. First, we present a dataset of cryptic clues as a challenging new benchmark for NLP systems that seek to process compositional language in more creative, human-like ways. After showing that three non-neural approaches and T5, a state-of-the-art neural language model, do not achieve good performance, we make our second main contribution: a novel curriculum approach, in which the model is first fine-tuned on related tasks such as unscrambling words. We also introduce a challenging data split, examine ... : Please see the associated paper. ... Keyword: compositional; crossword; cryptic; FOS Computer and information sciences; NLP URL: http://datadryad.org/stash/dataset/doi:10.5061/dryad.n02v6wwzp https://dx.doi.org/10.5061/dryad.n02v6wwzp BASE Hide details 7 How (Non-)Optimal is the Lexicon? ... Pimentel, Tiago; Nikkarinen, Irene; Mahowald, Kyle. - : arXiv, 2021 BASE Show details

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