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JUICE: Unified Multimodal Modeling in Pretrained Representation Spaces
Author1, Author2, Author3, Author4, Author5
multimodalgenerative modelingjoint distributionvisual question answering
2610.28801
Builder Relevance
2h ago80%
Abstract
JUICE proposes a unified approach to multimodal modeling by generating images and text jointly from pretrained encoder spaces.
Reality Card
Core Claim
JUICE achieves a significant improvement in joint multimodal generation, reaching up to 0.88 on GenEval and 73.1 on VQAv2 without language model initialization.
Method / Result
Joint success in visual spatial planning rises from 54.6% with independent sampling to 93.7% with coupled sampling.
Limitations
The model's performance may vary based on the specific design choices made during controlled pretraining runs.
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