Universality and Limitations of Prompt Tuning

30 May 2023

Papers citing "Universality and Limitations of Prompt Tuning"

9 / 9 papers shown

Title
Efficient Knowledge Transfer in Multi-Task Learning through Task-Adaptive Low-Rank Representation Xiao Zhang Kangsheng Wang Tianyu Hu Huimin Ma 62 3 0 20 Apr 2025
NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models Yibo Zhong Haoxiang Jiang Lincan Li Ryumei Nakada Tianci Liu Linjun Zhang Huaxiu Yao Haoyu Wang 82 2 0 24 Feb 2025
AdaptGCD: Multi-Expert Adapter Tuning for Generalized Category Discovery Yuxun Qu Yongqiang Tang Chenyang Zhang Wensheng Zhang 31 0 0 29 Oct 2024
Parameter-Efficient Fine-Tuning of State Space Models Kevin Galim Wonjun Kang Yuchen Zeng H. Koo Kangwook Lee 31 4 0 11 Oct 2024
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization Yao Ni Shan Zhang Piotr Koniusz 172 2 0 25 Sep 2024
Differentially Private Kernel Density Estimation Erzhi Liu Jerry Yao-Chieh Hu Alex Reneau Zhao Song Han Liu 66 3 0 03 Sep 2024
Embedded Visual Prompt Tuning Wenqiang Zu Shenghao Xie Qing Zhao Guoqi Li Lei Ma VLM MedIm 54 9 0 01 Jul 2024
A Kernel-Based View of Language Model Fine-Tuning Sadhika Malladi Alexander Wettig Dingli Yu Danqi Chen Sanjeev Arora VLM 73 61 0 11 Oct 2022
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,858 0 18 Apr 2021