FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning

FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning

13 August 2021

Papers citing "FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning"

11 / 11 papers shown

Title
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models Ran Xu Hejie Cui Yue Yu Xuan Kan Wenqi Shi Yuchen Zhuang Wei Jin Joyce C. Ho Carl Yang 66 13 0 28 Jan 2025
Enhancing Few-Shot Image Classification through Learnable Multi-Scale Embedding and Attention Mechanisms Fatemeh Askari Amirreza Fateh Mohammad Reza Mohammadi 77 3 0 17 Jan 2025
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models Josip Jukić Jan Snajder 29 0 0 31 Mar 2024
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning Ananth Balashankar Xiao Ma Aradhana Sinha Ahmad Beirami Yao Qin Jilin Chen Alex Beutel 24 2 0 25 Oct 2023
Domain Adaptive Few-Shot Open-Set Learning Debabrata Pal Deeptej More Sai Bhargav Dipesh Tamboli Vaneet Aggarwal Biplab Banerjee 24 2 0 22 Sep 2023
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities Yisheng Song Ting-Yuan Wang S. Mondal J. P. Sahoo SLR 41 342 0 13 May 2022
Data Augmentation Approaches in Natural Language Processing: A Survey Bohan Li Yutai Hou Wanxiang Che 121 270 0 05 Oct 2021
Meta Pseudo Labels Hieu H. Pham Zihang Dai Qizhe Xie Minh-Thang Luong Quoc V. Le VLM 250 656 0 23 Mar 2020
Data Augmentation using Pre-trained Transformer Models Varun Kumar Ashutosh Choudhary Eunah Cho VLM 211 315 0 04 Mar 2020
Revisiting Self-Training for Neural Sequence Generation Junxian He Jiatao Gu Jiajun Shen MarcÁurelio Ranzato SSL LRM 242 269 0 30 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 6,950 0 20 Apr 2018