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SemEval-2022 Task 3: PreTENS-Evaluating Neural Networks on Presuppositional Semantic Knowledge.

, , , , , , and . SemEval@NAACL, page 228-238. Association for Computational Linguistics, (2022)

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An LSTM Adaptation Study of (Un)grammaticality., and . BlackboxNLP@ACL, page 204-212. Association for Computational Linguistics, (2019)SemEval-2022 Task 3: PreTENS-Evaluating Neural Networks on Presuppositional Semantic Knowledge., , , , , , and . SemEval@NAACL, page 228-238. Association for Computational Linguistics, (2022)Puzz-Ling: A hands-on model of syntax to popularize linguistics as a science., and . Lang. Linguistics Compass, (2018)SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment., , , , , and . SemEval@COLING, page 1-8. The Association for Computer Linguistics, (2014)One Picture and a Thousand Words. Generative Language+images Models and How to Train Them.. NL4AI@AI*IA, volume 3551 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)AcCompl-it @ EVALITA2020: Overview of the Acceptability & Complexity Evaluation Task for Italian., , , , , and . EVALITA, volume 2765 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Is Change the Only Constant? An Inquiry into Diachronic Semantic Shifts in Italian and Spanish., , and . CLiC-it, volume 3596 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Studying the Recursive Behaviour of Adjectival Modification with Compositional Distributional Semantics., , and . EMNLP, page 141-151. ACL, (2013)SICK through the SemEval glasses. Lesson learned from the evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment., , , , , and . Lang. Resour. Evaluation, 50 (1): 95-124 (2016)RNN Simulations of Grammaticality Judgments on Long-distance Dependencies., and . COLING, page 133-144. Association for Computational Linguistics, (2018)