Parameter-Efficient Tuning by Manipulating Hidden States of Pretrained
Language Models For Classification Tasks

Parameter-Efficient Tuning by Manipulating Hidden States of Pretrained Language Models For Classification Tasks

10 April 2022

Haoran Yang

Papers citing "Parameter-Efficient Tuning by Manipulating Hidden States of Pretrained Language Models For Classification Tasks"

7 / 7 papers shown

Title
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 236 780 0 14 Oct 2021
Is Attention Better Than Matrix Decomposition? Zhengyang Geng Meng-Hao Guo Hongxu Chen Xia Li Ke Wei Zhouchen Lin 48 134 0 09 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu Tianxiang Sun Yige Xu Yunfan Shao Ning Dai Xuanjing Huang LM&MA VLM 232 1,444 0 18 Mar 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 253 1,584 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 396 2,576 0 03 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 294 6,927 0 20 Apr 2018