DALLE-2 is Seeing Double: Flaws in Word-to-Concept Mapping in Text2Image Models
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Abstract (arXiv)
We study the way DALLE-2 maps symbols (words) in the prompt to their references (entities or properties of entities in the generated image). We show that in stark contrast to the way human process language, DALLE-2 does not follow 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 set of stimuli that reflect the phenomenon: we show that DALLE-2 depicts both senses of nouns with multiple senses at once; and that a given word can modify the properties of two distinct entities in the image, or can be depicted as one object and also modify the properties of another object, creating a semantic leakage of properties between entities. Taken together, our study highlights the differences between DALLE-2 and human language processing and opens an avenue for future study on the inductive biases of text-to-image models.
Key facts. Cited by 50 papers in the map (data through 7 Oct 2026). Builds on 6 of its 11 references that are in the map. First posted on arXiv 19 Oct 2022.
Builds on
6 of 11 references.
References · 6
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
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- 2022A very preliminary analysis of DALL-E 2cited by 82
- 2022Testing Relational Understanding in Text-Guided Image Generationcited by 59
- 2022Underspecification in Scene Description-to-Depiction Taskscited by 30
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Citing papers per year: 2022: 4; 2023: 15; 2024: 19; 2025: 7; 2026: 5.
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- 2024Swing-by Dynamics in Concept Learning and Compositional Generalization10 Oct 2024
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- 2024DiffusionPID: Interpreting Diffusion via Partial Information Decomposition7 Jun 2024
- 2024Text Guided Image Editing with Automatic Concept Locating and Forgetting30 May 2024
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- 2023Teaching CLIP to Count to Ten23 Feb 2023
- 2022When are Lemons Purple? The Concept Association Bias of Vision-Language Models22 Dec 2022
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- 2023Testing AI on language comprehension tasks reveals insensitivity to underlying meaningcited by 45
- 2024Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Spacecited by 33
- 2022DALL-E 2 Fails to Reliably Capture Common Syntactic Processescited by 31
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- 2025Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generation29 Mar 2025
- 2025Scaling Down Semantic Leakage: Investigating Associative Bias in Smaller Language Models11 Jan 2025
- 2024EvalGIM: A Library for Evaluating Generative Image Models13 Dec 2024
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