Adversarial Error Correction for Visual Autoregressive Generation 事件

Adversarial Error Correction for Visual Autoregressive Generation arXiv:2605.24843v1 Announce Type: new Abstract: Visual Autoregressive (VAR) models have emerged as a powerful paradigm for image synthesis by performing hierarchical next-scale prediction. However, VAR models are inherently prone to cascading error propagation, where subtle coarse-scale mispredictions are amplified across the hierarchy, ultimately distorting the final synthesis. To mitigate this, we propose AID-VAR, a plug-and-pl