Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning

  title={Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning},
  author={Rongzhi Zhang and Yue Yu and Pranav Shetty and Le Song and Chao Zhang},
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult. We study interactive weakly-supervised learning—the problem of iteratively and automatically discovering novel labeling rules from data to improve the WSL model. Our proposed model, named PRBoost, achieves this goal via iterative prompt-based rule discovery and model boosting. It uses… 

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