Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank
Prompt Adaptation

Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation

24 May 2024

Abhinav C. P. Jain

Swarat Chaudhuri

Christopher M. Jermaine

Papers citing "Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation"

6 / 6 papers shown

Title
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Zeyu Han Chao Gao Jinyang Liu Jeff Zhang Sai Qian Zhang 150 310 0 21 Mar 2024
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 238 806 0 14 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
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters Aston Zhang Yi Tay Shuai Zhang Alvin Chan A. Luu S. Hui Jie Fu MQ 182 83 0 17 Feb 2021
WARP: Word-level Adversarial ReProgramming Karen Hambardzumyan Hrant Khachatrian Jonathan May AAML 254 342 0 01 Jan 2021
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