ReAlign corrects the modality gap in unpaired data to let MLLMs learn visual distributions from text alone before instruction tuning, reducing dependence on expensive paired corpora.
Learn to explain: Multimodal reasoning via thought chains for science question answering
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Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models
ReAlign corrects the modality gap in unpaired data to let MLLMs learn visual distributions from text alone before instruction tuning, reducing dependence on expensive paired corpora.