Can Large Language Models Design Accurate Label Functions?. (arXiv:2311.00739v1 [cs.CL])

Programmatic weak supervision methodologies facilitate the expedited labeling
of extensive datasets through the use of label functions (LFs) that encapsulate
heuristic data sources. Nonetheless, the creation of precise LFs necessitates
domain expertise and substantial endeavors. Recent advances in pre-trained
language models (PLMs) have exhibited substantial potential across diverse
tasks. However, the capacity of PLMs to autonomously formulate accurate LFs
remains an underexplored domain. In this research, we address this gap by
introducing DataSculpt, an interactive framework that harnesses PLMs for …

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