FPT: Improving Prompt Tuning Efficiency via Progressive Training

FPT: Improving Prompt Tuning Efficiency via Progressive Training

13 November 2022

Maosong Sun

Zhiyuan Liu

Qun Liu

Papers citing "FPT: Improving Prompt Tuning Efficiency via Progressive Training"

7 / 7 papers shown

Title
Enhancing Low-Resource Relation Representations through Multi-View Decoupling Chenghao Fan Wei Wei Xiaoye Qu Zhenyi Lu Wenfeng Xie Yu Cheng Dangyang Chen 26 2 0 26 Dec 2023
Adaptive Shortcut Debiasing for Online Continual Learning Doyoung Kim Dongmin Park Yooju Shin Jihwan Bang Hwanjun Song Jae-Gil Lee CLL 52 2 0 14 Dec 2023
FedYolo: Augmenting Federated Learning with Pretrained Transformers Xuechen Zhang Mingchen Li Xiangyu Chang Jiasi Chen A. Roy-Chowdhury A. Suresh Samet Oymak FedML 31 7 0 10 Jul 2023
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer Tu Vu Brian Lester Noah Constant Rami Al-Rfou Daniel Cer VLM LRM 137 277 0 15 Oct 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
On the Transformer Growth for Progressive BERT Training Xiaotao Gu Liyuan Liu Hongkun Yu Jing Li Cheng Chen Jiawei Han VLM 66 51 0 23 Oct 2020
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 153 345 0 23 Jul 2020