MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts
arXiv cs.CV1mo4 min read
arXiv:2607.00371v1 Announce Type: new Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities in image generation. However, VAR still suffers from inherent deficiencies in multi-scale representation learning. Specifically, lower scales primarily capture global semantics, while higher scales focus on fine-grained details. Employing a shared architecture across scales induces optimization conflicts. Moreover, due to the causal autoregressive process, inaccurate semantics at early scales can pr
