BriefGPT.xyz
Apr, 2024
从模型性能到声明:机器学习可复现性的焦点转变如何帮助弥合责任鸿沟
From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap
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Tianqi Kou
TL;DR
通过将模型性能可复制性转变为主张可复制性,可以使机器学习科学家对产生不可复制的主张负责并对其造成的滥用和误解负责,从而缩小责任差距。
Abstract
Two goals - improving
replicability
and
accountability
of
machine learning
research respectively, have accrued much attention from the AI
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