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Visually-Grounded Planning without Vision: Language Models Infer Detailed Plans from High-level Instructions.. EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 4412-4417. Association for Computational Linguistics, (2020)Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing., and . Connect. Sci., 24 (1): 25-55 (2012)CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and Generalization., , , , , , , and . CoRR, (2023)Multi-class Hierarchical Question Classification for Multiple Choice Science Exams., , , , , , , and . CoRR, (2019)A Systematic Survey of Text Worlds as Embodied Natural Language Environments.. CoRR, (2021)Multi-class Hierarchical Question Classification for Multiple Choice Science Exams., , , , , , , and . LREC, page 5370-5382. European Language Resources Association, (2020)WorldTree V2: A Corpus of Science-Domain Structured Explanations and Inference Patterns supporting Multi-Hop Inference., , , , , and . LREC, page 5456-5473. European Language Resources Association, (2020)Self-Supervised Behavior Cloned Transformers are Path Crawlers for Text Games., and . EMNLP (Findings), page 5555-5565. Association for Computational Linguistics, (2023)ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games., , , , , and . EMNLP, page 13455-13471. Association for Computational Linguistics, (2023)WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-Hop Inference., , , and . CoRR, (2018)