This paper proposes a new framework for joint multimodal representation learning and generation, allowing for flexible-length aligned transmodal tokens that can be used for both retrieval and generation tasks. Practitioners might care about this paper because it shows how to improve generative performance by training a shared multimodal encoder alongside downstream models.
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