The paper proposes six curriculum sampling strategies driven by a pretrained language model's own prompt-based confidence scores and reports mixed, mostly small, improvements over random sampling on four NLU datasets.
Cunningham, Dominique Archambault, and Austin Kung
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Your Pretrained Model Tells the Difficulty Itself: A Self-Adaptive Curriculum Learning Paradigm for Natural Language Understanding
The paper proposes six curriculum sampling strategies driven by a pretrained language model's own prompt-based confidence scores and reports mixed, mostly small, improvements over random sampling on four NLU datasets.