MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

19 April 2023

Yutai Hou

Papers citing "MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning"

8 / 8 papers shown

Title
PromptDA: Label-guided Data Augmentation for Prompt-based Few-shot Learners Canyu Chen Kai Shu VLM 18 8 0 18 May 2022
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning Jishnu Ray Chowdhury Yong Zhuang Shuyi Wang 123 39 0 01 Feb 2022
Data Augmentation Approaches in Natural Language Processing: A Survey Bohan Li Yutai Hou Wanxiang Che 113 269 0 05 Oct 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
WARP: Word-level Adversarial ReProgramming Karen Hambardzumyan Hrant Khachatrian Jonathan May AAML 243 340 0 01 Jan 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
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 391 2,216 0 03 Sep 2019