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Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering., , , and . CoRR, (2020)Latent Trees for Compositional Generalization., , and . Compendium of Neurosymbolic Artificial Intelligence, volume 369 of Frontiers in Artificial Intelligence and Applications, IOS Press, (2023)Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data., , and . CoRR, (2021)Evaluating Models' Local Decision Boundaries via Contrast Sets., , , , , , , , , and 16 other author(s). EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 1307-1323. Association for Computational Linguistics, (2020)Grammar-based Neural Text-to-SQL Generation., , , , and . CoRR, (2019)Language Generation with Recurrent Generative Adversarial Networks without Pre-training., , , , and . CoRR, (2017)Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering., , , and . Trans. Assoc. Comput. Linguistics, (2021)Leveraging Code to Improve In-context Learning for Semantic Parsing., , , and . CoRR, (2023)COVR: A Test-Bed for Visually Grounded Compositional Generalization with Real Images., , , and . EMNLP (1), page 9824-9846. Association for Computational Linguistics, (2021)Diverse Demonstrations Improve In-context Compositional Generalization., , and . CoRR, (2022)