MAR-MAER: Metric-Aware and Ambiguity-Adaptive Autoregressive Image Generation
Autoregressive (AR) models have demonstrated significant success in the realm of text-to-image generation. However, they usually face two major challenges. Firstly, the generated images may not always meet the quality standards expected by humans. Furthermore, these models face difficulty when dealing with ambiguous prompts that could be interpreted in several valid ways. To address these issues, we introduce MAR-MAER, an innovative hierarchical autoregressive framework. It combines two main components. It is a metric-aware embedding regularization method. The other one is a probabilistic latent model used for handling ambiguous semantics. Our method utilizes a lightweight projection head...
| Authors | Kai Dong, Tingting Bai |
|---|---|
| Primary category | cs.CV |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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