Catherine Henry
2023
Tiny Language Models Enriched with Multimodal Knowledge from Multiplex Networks
Clayton Fields
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Osama Natouf
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Andrew McMains
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Catherine Henry
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Casey Kennington
Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
2022
Symbol and Communicative Grounding through Object Permanence with a Mobile Robot
Josue Torres-Fonseca
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Catherine Henry
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Casey Kennington
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
Object permanence is the ability to form and recall mental representations of objects even when they are not in view. Despite being a crucial developmental step for children, object permanence has had only some exploration as it relates to symbol and communicative grounding in spoken dialogue systems. In this paper, we leverage SLAM as a module for tracking object permanence and use a robot platform to move around a scene where it discovers objects and learns how they are denoted. We evaluated by comparing our system’s effectiveness at learning words from human dialogue partners both with and without object permanence. We found that with object permanence, human dialogue partners spoke with the robot and the robot correctly identified objects it had learned about significantly more than without object permanence, which suggests that object permanence helped facilitate communicative and symbol grounding.
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