Papers with one-to-one image-caption paradigm

1 papers
Seeing Through Words, Speaking Through Pixels: Deep Representational Alignment Between Vision and Language Models (2025.emnlp-main)

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Challenge: Recent studies show that deep vision-only and language-only models project inputs into a partially aligned representational space.
Approach: They investigate whether a model's representational code is semantically shared . they find that alignment peaks in mid-to-late layers of both model types .
Outcome: a forced-choice "Pick-a-Pic" task shows human preferences for image-caption matches are mirrored in embedding spaces across vision-language model pairs.

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