Google AI 提出了擴散模型中推理時間縮放的基本框架
來自紐約大學、麻省理工學院和谷歌的研究團隊近日提出了一個創新框架，旨在解決擴散模型在推理時間擴展方面的瓶頸問題。這一突破性研究超越了傳統簡單增加去噪步驟的方法，爲提升生成模型性能開闢了新途徑。該框架主要從兩個維度展開:一是利用驗證器提供反饋，二是實施算法以發現更優的噪聲候選。研究團隊以256×256分辨率的預訓練SiT-XL模型爲基礎，在保持250個固定去噪步驟的同時，創新性地引入了專用於搜索操作的額外計算資源。在驗證系統方面，研究採用了兩個Oracle Verifie
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