Fighting Randomness with Randomness: Mitigating Optimisation Instability
of Fine-Tuning using Delayed Ensemble and Noisy Interpolation

Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation

18 June 2024

Branislav Pecher

Róbert Belanec

Jakub Simko

Papers citing "Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation"

6 / 6 papers shown

Title
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer Lichang Chen Heng-Chiao Huang Varun Madhavan AAML 116 11 0 03 May 2023
Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data Stephen Obadinma Hongyu Guo Xiao-Dan Zhu 27 2 0 05 Mar 2023
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning Runxin Xu Fuli Luo Zhiyuan Zhang Chuanqi Tan Baobao Chang Songfang Huang Fei Huang LRM 145 178 0 13 Sep 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
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models Cheolhyoung Lee Kyunghyun Cho Wanmo Kang MoE 249 205 0 25 Sep 2019
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