SOURCE-LINKED INTELLIGENCE
There and Back Again: Bidirectional Diffusion Bridges for Multimodality Translation
Multimodality translation (e.g., text-to-image) is a core generative AI task. However, existing approaches (1) follow generative paths that do not directly represent the source modality, limiting the flexibility of some sampling algorithms; and (2) are unidirectional, preventing inversion (e.g., image-to-text). We propose BIT: Bidirectional Image-Text Diffusion Bridges. In contrast to previous approaches, BIT starts directly from text and interpolates into images, providing (1) a source-aware generative path that enables diverse and flexible sampling algorithms; and (2) an endpoint-conditioned
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T03:43:53.000Z
First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.