FlexUMM: Flexible Representation Learning for Unified Multimodal Models
In brief
- FlexUMM optimizes representation sharing between understanding and generation in UMMs.
- The method reduces conflicts between functionalities and avoids unnecessary computations.
- The code is open-sourced and compatible with existing UMMs.
FlexUMM introduces a flexible framework for unified multimodal models (UMMs) that optimizes representation sharing between understanding and generation. The approach enhances both accuracy and efficiency by dynamically adapting processing based on task-specific needs. The code is released as open source.
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