A cost-effective dataset framework for English AI tutoring finds that mixing 5-10% human-annotated feedback with LLM-generated feedback outperforms using only human-annotated feedback.
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FEAT: A Preference Feedback Dataset through a Cost-Effective Auto-Generation and Labeling Framework for English AI Tutoring
A cost-effective dataset framework for English AI tutoring finds that mixing 5-10% human-annotated feedback with LLM-generated feedback outperforms using only human-annotated feedback.