A Computational Acquisition Model for Multimodal Word Categorization (2022.naacl-main)
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| Challenge: | Recent advances in self-supervised modeling of text and images open new opportunities for computational models of child language acquisition. |
| Approach: | They propose a multimodal language acquisition model trained from image-caption pairs on naturalistic data using cross-modal self-supervision. |
| Outcome: | The proposed model learns word categories and object recognition abilities, the authors show . their model is trained from image-caption pairs on naturalistic data using cross-modal self-supervision . |
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