Reliable Gradient-free and Likelihood-free Prompt Tuning

30 April 2023

Papers citing "Reliable Gradient-free and Likelihood-free Prompt Tuning"

9 / 9 papers shown

Title
When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges Wang Chao Jiaxuan Zhao Licheng Jiao Lingling Li Fang Liu Shuyuan Yang 75 13 0 19 Jan 2024
A Bayesian approach for prompt optimization in pre-trained language models Antonio Sabbatella Andrea Ponti Antonio Candelieri I. Giordani Francesco Archetti 47 1 0 01 Dec 2023
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 240 822 0 14 Oct 2021
Types of Out-of-Distribution Texts and How to Detect Them Udit Arora William Huang He He OODD 227 97 0 14 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 298 3,906 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 245 1,941 0 31 Dec 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 250 293 0 17 Mar 2020
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 316 7,044 0 20 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 295 5,726 0 05 Dec 2016