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We study the way DALLE-2 maps symbols (words) in the prompt to theirreferences (entities or properties of entities in the generated image). We showthat in stark contrast to the way human process language, DALLE-2 does notfollow the constraint that each word has a single role in the interpretation,and sometimes re-use the same symbol for different purposes. We collect a setof stimuli that reflect the phenomenon: we show that DALLE-2 depicts bothsenses of nouns with multiple senses at once; and that a given word can modifythe properties of two distinct entities in the image, or can be depicted as oneobject and also modify the properties of another object, creating a semanticleakage of properties between entities. Taken together, our study highlightsthe differences between DALLE-2 and human language processing and opens anavenue for future study on the inductive biases of text-to-image models.

DALLE-2 is Seeing Double: Flaws in Word-to-Concept Mapping in Text2Image Models