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Calibrated Ambiguity in Multimodal Language Models: Humans reach for cultural references, while models describe the picture

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

Ambiguity is often treated as a bug for AI systems to resolve---but in human communication and culture, ambiguity can also be a generative resource. From humour to politics to art, people express themselves in words and images that are open enough to invite different interpretations, yet constrained enough to be interpretable. We operationalise this notion of calibrated ambiguity with a task drawn from the parlour game Dixit. We compare differences in clues generated by human vs multimodal language models, based on a novel coding rubric for calibrated ambiguity, and find that models consistent

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