The Auto-Rubric as Reward (ARR) framework enhances multimodal generative models by transforming implicit preferences into explicit, structured rubrics, improving alignment with human judgment. This approach shows promise in generating more reliable and data-efficient outcomes in text-to-image generation and image editing tasks, outperforming traditional reward models.