Papers with vision-aligned task

1 papers
VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation (2026.acl-long)

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Challenge: Multimodal large language models have advanced rapidly, yet most remain English-centric . scaling multilingual multimodal instruction tuning is limited by the scarcity and high cost of non-English image–text supervision.
Approach: They propose a framework that decouples multilingual language enhancement from visual alignment by composing complementary task vectors over a shared LLM backbone.
Outcome: The proposed framework achieves competitive performance with a fully multimodally trained model using less than 2% of the text data.

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