1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025
ScriptoriumWS: A Code Generation Assistant for Weak Supervision
Tzu-Heng Huang, Catherine Cao, Spencer Schoenberg +3
Weak supervision is a popular framework for overcoming the labeled data bottleneck: the need to obtain labels for training data. In weak supervision, multiple noisy-but-cheap sourc…
cs.LG2022★ 1 cited
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels
Nicholas Roberts, Xintong Li, Tzu-Heng Huang +7
Weak supervision (WS) is a powerful method to build labeled datasets for training supervised models in the face of little-to-no labeled data. It replaces hand-labeling data with ag…