Data Augmentation Approaches in Natural Language Processing: A Survey

Data Augmentation Approaches in Natural Language Processing: A Survey

5 October 2021

Yutai Hou

Papers citing "Data Augmentation Approaches in Natural Language Processing: A Survey"

8 / 8 papers shown

Title
Internet-Augmented Dialogue Generation M. Komeili Kurt Shuster Jason Weston RALM 207 238 0 15 Jul 2021
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation Ieva Staliunaite P. Gorinski Ignacio Iacobacci LRM 98 18 0 13 Jan 2021
Substructure Substitution: Structured Data Augmentation for NLP Freda Shi Karen Livescu Kevin Gimpel 148 39 0 02 Jan 2021
Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation Alexander R. Fabbri Simeng Han Haoyuan Li Haoran Li Marjan Ghazvininejad Shafiq R. Joty Dragomir R. Radev Yashar Mehdad 86 82 0 24 Oct 2020
Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering Arij Riabi Thomas Scialom Rachel Keraron Benoît Sagot Djamé Seddah Jacopo Staiano 109 45 0 23 Oct 2020
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding Yanru Qu Dinghan Shen Yelong Shen Sandra Sajeev Jiawei Han Weizhu Chen 99 59 0 16 Oct 2020
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks Nandan Thakur Nils Reimers Johannes Daxenberger Iryna Gurevych 163 190 0 16 Oct 2020
Data Augmentation using Pre-trained Transformer Models Varun Kumar Ashutosh Choudhary Eunah Cho VLM 190 315 0 04 Mar 2020