PEFTT: Parameter-Efficient Fine-Tuning for low-resource Tibetan pre-trained language models

21 September 2023

Papers citing "PEFTT: Parameter-Efficient Fine-Tuning for low-resource Tibetan pre-trained language models"

6 / 6 papers shown

Title
TiBERT: Tibetan Pre-trained Language Model Yuan Sun Sisi Liu Junjie Deng Xiaobing Zhao 54 9 0 15 May 2022
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer Tu Vu Brian Lester Noah Constant Rami Al-Rfou Daniel Matthew Cer VLM LRM 137 277 0 15 Oct 2021
RAFT: A Real-World Few-Shot Text Classification Benchmark Neel Alex Eli Lifland Lewis Tunstall A. Thakur Pegah Maham ... Carolyn Ashurst Paul Sedille A. Carlier M. Noetel Andreas Stuhlmuller RALM 173 56 0 28 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,835 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,913 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,584 0 21 Jan 2020