Google AI 提出了扩散模型中推理时间缩放的基本框架
来自纽约大学、麻省理工学院和谷歌的研究团队近日提出了一个创新框架，旨在解决扩散模型在推理时间扩展方面的瓶颈问题。这一突破性研究超越了传统简单增加去噪步骤的方法，为提升生成模型性能开辟了新途径。该框架主要从两个维度展开:一是利用验证器提供反馈，二是实施算法以发现更优的噪声候选。研究团队以256×256分辨率的预训练SiT-XL模型为基础，在保持250个固定去噪步骤的同时，创新性地引入了专用于搜索操作的额外计算资源。在验证系统方面，研究采用了两个Oracle Verifie
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