A Survey on Programmatic Weak Supervision

A Survey on Programmatic Weak Supervision

11 February 2022

Alexander Ratner

Papers citing "A Survey on Programmatic Weak Supervision"

7 / 57 papers shown

Title
Language Models in the Loop: Incorporating Prompting into Weak Supervision Ryan Smith Jason Alan Fries Braden Hancock Stephen H. Bach 35 52 0 04 May 2022
Satellite Monitoring of Terrestrial Plastic Waste C. Kruse Edward Boyda Sully Chen Krishna Karra Tristan Bou-Nahra D. Hammer J. Mathis Taylor Maddalene J. Jambeck F. Laurier 14 12 0 24 Mar 2022
Generative Modeling Helps Weak Supervision (and Vice Versa) Benedikt Boecking Nicholas Roberts W. Neiswanger Stefano Ermon Frederic Sala Artur Dubrawski 12 1 0 22 Mar 2022
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning Rongzhi Zhang Yue Yu Pranav Shetty Le Song Chao Zhang 25 23 0 18 Mar 2022
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming Cheng-Yu Hsieh Jieyu Zhang Alexander Ratner 18 15 0 02 Mar 2022
Creating Training Sets via Weak Indirect Supervision Jieyu Zhang Bohan Wang Xiangchen Song Yujing Wang Yaming Yang Jing Bai Alexander Ratner OffRL 43 17 0 07 Oct 2021
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 235 319 0 21 Aug 2019