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Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning

Amogh Inamdar, Zhenwei Tang, Ashton Anderson, Richard Zemel
Jun 5, 2026 at 04:00
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arXiv:2603.13761v2 Announce Type: replace-cross Abstract: Curriculum learning--ordering training examples in a sequence to aid machine learning--takes inspiration from human learning, but has not gained widespread acceptance. Static strategies for scoring item difficulty rely on indirect proxy scores of varying quality and produce curricula that...

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