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How Can Memory-Augmented Neural Networks Pass a False-Belief Task?

, , and . CogSci, cognitivesciencesociety.org, (2017)

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How FaR Are Large Language Models From Agents with Theory-of-Mind?, , , , , , , , , and 2 other author(s). CoRR, (2023)A Computational Model of Memory, Attention, and Word Learning., , and . CMCL@NAACL-HLT, page 80-89. Association for Computational Linguistics, (2012)Word Learning in the Wild: What Natural Data Can Tell Us., , , and . CogSci, cognitivesciencesociety.org, (2013)Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings., , , , , , , , , and 1 other author(s). CoRR, (2024)Evaluating Numerical Reasoning in Text-to-Image Models., , , , , , and . CoRR, (2024)Computational Modeling of Word Learning: The Role of Cognitive Processes.. University of Toronto, Canada, (2016)Vision-Language Pretraining: Current Trends and the Future., , and . ACL (tutorial), page 38-43. Association for Computational Linguistics, (2022)Simple Search Algorithms on Semantic Networks Learned from Language Use., , and . CogSci, cognitivesciencesociety.org, (2016)Calculating Probabilities Simplifies Word Learning., , , and . CogSci, cognitivesciencesociety.org, (2017)Mutual Exclusivity as Competition in Cross-situational Word Learning., , , and . CogSci, cognitivesciencesociety.org, (2021)