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The neural dynamics of word recognition and integration.

, and . EMNLP, page 980-995. Association for Computational Linguistics, (2023)

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Speakers optimize information density through syntactic reduction, and . Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, (2007)Eye movement evidence that readers maintain and act on uncertainty about past linguistic input, , , and . Proceedings of the National Academy of Sciences, 106 (50): 21086-21090 (December 2009)On the Effect of Anticipation on Reading Times., , , , and . CoRR, (2022)Language model acceptability judgements are not always robust to context., , , , , , and . CoRR, (2022)Expectations over Unspoken Alternatives Predict Pragmatic Inferences., , , and . CoRR, (2023)Language Learning and Processing in People and Machines., , and . NAACL-HLT (Tutorial Abstracts), page 19-21. Association for Computational Linguistics, (2019)Data-driven learning of symbolic constraints for a log-linear model in a phonological setting., and . COLING, page 2217-2226. ACL, (2016)Automated Whole Sentence Grammar Correction Using a Noisy Channel Model., and . ACL, page 934-944. The Association for Computer Linguistics, (2011)Structural Guidance for Transformer Language Models., , , and . ACL/IJCNLP (1), page 3735-3745. Association for Computational Linguistics, (2021)Noisy-context surprisal as a human sentence processing cost model., and . EACL (1), page 688-698. Association for Computational Linguistics, (2017)