PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models

PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models

22 October 2022

Zhoujun Li

Papers citing "PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models"

5 / 5 papers shown

Title
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration Xinghao Wu Xuefeng Liu Jianwei Niu Guogang Zhu Shaojie Tang FedML 21 17 0 20 Sep 2023
Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu Tianxiang Sun Yige Xu Yunfan Shao Ning Dai Xuanjing Huang LM&MA VLM 243 1,452 0 18 Mar 2020
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 223 438 0 25 Sep 2019
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