LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot
Learners

LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot Learners

12 October 2021

Yaqing Wang

Subhabrata Mukherjee

Xiaodong Liu

Jing Gao

Ahmed Hassan Awadallah

Papers citing "LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot Learners"

8 / 8 papers shown

Title
Late Prompt Tuning: A Late Prompt Could Be Better Than Many Prompts Xiangyang Liu Tianxiang Sun Xuanjing Huang Xipeng Qiu VLM 36 27 0 20 Oct 2022
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning Tu Vu Minh-Thang Luong Quoc V. Le Grady Simon Mohit Iyyer 128 60 0 13 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,848 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,919 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,589 0 21 Jan 2020
Revisiting Self-Training for Neural Sequence Generation Junxian He Jiatao Gu Jiajun Shen MarcÁurelio Ranzato SSL LRM 244 269 0 30 Sep 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017