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Jul, 2024
迈向可扩展的无参考生成模型评估
Towards a Scalable Reference-Free Evaluation of Generative Models
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Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov...
TL;DR
我们提出了傅里叶基核熵估计(FKEA)方法,利用FKEA的近似特征谱来高效估计生成数据的多样性评分,并展示了其在大规模生成模型评估中的可扩展性和解释性。
Abstract
While standard evaluation scores for
generative models
are mostly reference-based, a reference-dependent assessment of
generative models
could be generally difficult due to the unavailability of applicable refere
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