AutoRubric-T2I: Robust Rule-Based Reward Model for Text-to-Image Alignment

In three linesAutoRubric-T2I automatically synthesizes explicit rubrics to guide Vision-Language Model judges for text-to-image alignment evaluation. Using <0.01% of annotation data required by traditional reward models, it outperforms baselines on MMRB2 and improves generation quality with Flow-GRPO on diffusion models.

Summary generated by Claude — human-verified