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cs.CV2025
Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation
Taeyoung Yun, Dinghuai Zhang, Jinkyoo Park +1
Recent advances in text-to-image diffusion models have achieved impressive image generation capabilities. However, it remains challenging to control the generation process with des…
cs.CV2024
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation
Jiatao Gu, Yuyang Wang, Yizhe Zhang +5
Diffusion models have become the dominant approach for visual generation. They are trained by denoising a Markovian process which gradually adds noise to the input. We argue that t…