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Speakers optimize information density through syntactic reduction, and . Advances in Neural Information Processing Systems 19, MIT Press, Cambridge, MA, (2007)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)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)Language Learning and Processing in People and Machines., , and . NAACL-HLT (Tutorial Abstracts), page 19-21. Association for Computational Linguistics, (2019)What do RNN Language Models Learn about Filler-Gap Dependencies?, , , and . BlackboxNLP@EMNLP, page 211-221. Association for Computational Linguistics, (2018)A Noisy-Channel Model of Human Sentence Comprehension under Uncertain Input.. EMNLP, page 234-243. ACL, (2008)Noisy-context surprisal as a human sentence processing cost model., and . EACL (1), page 688-698. Association for Computational Linguistics, (2017)Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization., , and . BlackboxNLP@EMNLP, page 265-275. Association for Computational Linguistics, (2020)