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

18 March 2022

Papers citing "PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning"

6 / 6 papers shown

Title
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels Nicholas Roberts Xintong Li Tzu-Heng Huang Dyah Adila Spencer Schoenberg Chengao Liu Lauren Pick Haotian Ma Aws Albarghouthi Frederic Sala UQCV 14 7 0 30 Aug 2022
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 228 780 0 14 Oct 2021
PTR: Prompt Tuning with Rules for Text Classification Xu Han Weilin Zhao Ning Ding Zhiyuan Liu Maosong Sun VLM 31 510 0 24 May 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 275 3,784 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 238 1,898 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 248 1,382 0 21 Jan 2020