Seeing Is Not Sharing: Some Vision-Language Models Overestimate Common Ground in Asymmetric Dialogue

Researchers from Utrecht University investigated whether vision-language models can distinguish shared from interpreted visual information in dialogue. They found that providing authentic map images improves model performance but introduces a bias toward over-predicting alignment between participants.

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