Decoupled Vision-Language System for Multimodal Understanding and Generation
We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Libra architecture contains one vision system and one language system, connected by cross-modal bridges. This design decouples self-modal modeling and cross-modal interaction, enabling each modality to learn its unique representations while maintaining effective cross-modal comprehension. The decoupling is mainly achieved in a switch attention module and a switch FFN module, which dynamically routes the computation flow for self-modal modeling and cross-modal interaction scenarios. We evaluate the effectiveness in two important settings: \tex...
| Authors | Yifan Xu, Baochen Xiong, Xiaoshan Yang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 29 June 2026 |
| Last updated at source | 29 June 2026 |
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