BriefGPT.xyz
Jun, 2023
学习无效数据:生成模型中的约束满足问题
Learning from Invalid Data: On Constraint Satisfaction in Generative Models
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Giorgio Giannone, Lyle Regenwetter, Akash Srivastava, Dan Gutfreund, Faez Ahmed
TL;DR
通过提出一种新的训练机制来提高生成模型的精度,该机制利用了约束违规的数据扩展了标准模型的数据集,我们的方法使生成分布与有效先验之间的差异最小化,同时最大化与无效分布之间的差异。
Abstract
generative models
have demonstrated impressive results in vision, language, and speech. However, even with massive datasets, they struggle with
precision
, generating physically invalid or factually incorrect data
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