Papers with text-only counterparts

1 papers
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation (2021.acl-long)

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Challenge: Recent studies report improvements when equipping models with multimodal information, but it remains unclear whether such improvements actually come from the multimodal part.
Approach: They propose to extend conventional text-only translation models with multimodal information by extending them with visual input.
Outcome: The proposed models replicate similar gains as recently developed multimodal-integrated systems achieved, but learn to ignore multimodal information.

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