Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs). Reconstructive post-training couples these tasks, but existing reconstruction-based methods remain perception-centric and provide limited supervision for reasoning about structure, intent, and transf...
Fei-Ze Wu, Zhi-Yuan Yan, Yuri Hong et al.· 0 citations
Patch Reparameterization is introduced, which preserves the original semantic pathway while adding a reconstruction-aware patch embedding that provides fine-grained visual information to the same frozen ViT blocks, and preserves multimodal understanding while enabling high-fidelity image reconstruction and a favorable...
Jinbo Yan, Limeng Qiao, Jie Qin et al.· 0 citations
Through an exhaustive evaluation of over 20 state-of-the-art MLLMs, HoloCount reveals a critical performance gap: even top-tier models degrade significantly as tasks transition from perception to complex analytical reasoning and adverse scenarios.