Papers with text-to-image retrieval paradigm

1 papers
Vision-Free Retrieval: Rethinking Multimodal Search with Textual Scene Descriptions (2025.emnlp-main)

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Challenge: Contrastively trained Vision-Language Models exhibit shallow language understanding, manifesting bag-of-words behaviour.
Approach: They propose a vision-free, single-encoder retrieval pipeline to replace traditional text-to-image retrieval paradigm with structured image descriptions.
Outcome: The proposed approach reduces the modality gap and improves compositionality and performance on short and long caption queries.

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