Analyzing DINOv2 embeddings shows that visual distance in a self-supervised space correlates with how adults extend new words to objects. Results suggest that the composition of training examples—whether they are superordinate or subordinate—dramatically affects how broadly a word is applied.
HOW THIS AFFECTS YOU
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researcherYou can use these findings to understand how visual feature similarity affects the way models or humans learn categories.