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DiverseVAR: Balancing Diversity and Quality of Next-Scale Visual Autoregressive Models
We introduce DiverseVAR, a framework that enhances the diversity of text-conditioned visual autoregressive models (VAR) at test time without requiring retraining, fine-tuning, or substantial computational overhead. While VAR models have recently emerged as strong competitors to diffusion and flow mo
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