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Improving event prediction by representing script participants., и . HLT-NAACL, стр. 546-551. The Association for Computational Linguistics, (2016)Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification., и . IWCS (1), стр. 188-199. Association for Computational Linguistics, (2019)G-TUNA: a corpus of referring expressions in German, including duration information., , и . INLG, стр. 149-153. Association for Computational Linguistics, (2017)Psycholinguistic Models of Sentence Processing Improve Sentence Readability Ranking., и . EACL (1), стр. 958-968. Association for Computational Linguistics, (2017)Improving Zero-Shot Multilingual Text Generation via Iterative Distillation., , и . COLING, стр. 5876-5881. International Committee on Computational Linguistics, (2022)Improving fit to human reading times via temperature-scaled surprisal., , и . CoRR, (2023)Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training., , , и . AfricaNLP, (2020)Incremental Neo-Davidsonian semantic construction for TAG., и . TAG, стр. 64-72. ACL, (2012)The semantic augmentation of a psycholinguistically-motivated syntactic formalism., и . CMCL, стр. 57-65. Association for Computational Linguistics, (2013)Vector-space calculation of semantic surprisal for predicting word pronunciation duration., , и . ACL (1), стр. 763-773. The Association for Computer Linguistics, (2015)