55 citations · 55 across the 3 of their papers we have counts for
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cs.LG2024
Leveraging Large Language Models for Structure Learning in Prompted Weak Supervision
Jinyan Su, Peilin Yu, Jieyu Zhang +1
Prompted weak supervision (PromptedWS) applies pre-trained large language models (LLMs) as the basis for labeling functions (LFs) in a weak supervision framework to obtain large la…
cs.LG2023
Alfred: A System for Prompted Weak Supervision
Peilin Yu, Stephen H. Bach
Alfred is the first system for programmatic weak supervision (PWS) that creates training data for machine learning by prompting. In contrast to typical PWS systems where weak super…
cs.LG2022★ 55 cited
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
Jessica Dai, Sohini Upadhyay, Ulrich Aivodji +2
As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting…