A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation

29 September 2020

Papers citing "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation"

22 / 22 papers shown

Title
Deterministic Reversible Data Augmentation for Neural Machine Translation Jiashu Yao Heyan Huang Zeming Liu Yuhang Guo 49 0 0 21 Feb 2025
Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification Guanyi Mou Yichuan Li Kyumin Lee 26 3 0 26 Sep 2024
Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation Jingxuan Wei Linzhuang Sun Yichong Leng Xu Tan Bihui Yu Ruifeng Guo 43 3 0 23 Apr 2024
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning Andrei Semenov Vladimir Ivanov Aleksandr Beznosikov Alexander Gasnikov 24 6 0 04 Apr 2024
Heterogeneous Contrastive Learning for Foundation Models and Beyond Lecheng Zheng Baoyu Jing Zihao Li Hanghang Tong Jingrui He VLM 30 19 0 30 Mar 2024
Retrofitting Light-weight Language Models for Emotions using Supervised Contrastive Learning Sapan Shah Sreedhar Reddy Pushpak Bhattacharyya 13 0 0 29 Oct 2023
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization Hyeon-Seob Kim Minsu Kim Sungsoo Ahn Jinkyoo Park OffRL 33 7 0 02 Jun 2023
"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion Zexue He An Yan Amilcare Gentili Julian McAuley Chun-Nan Hsu MedIm 14 2 0 15 May 2023
DropDim: A Regularization Method for Transformer Networks Hao Zhang Dan Qu Kejia Shao Xu Yang 20 12 0 20 Apr 2023
Steerable Equivariant Representation Learning Sangnie Bhardwaj Willie McClinton Tongzhou Wang Guillaume Lajoie Chen Sun Phillip Isola Dilip Krishnan OOD LLMSV 26 5 0 22 Feb 2023
Relaxed Attention for Transformer Models Timo Lohrenz Björn Möller Zhengyang Li Tim Fingscheidt KELM 24 11 0 20 Sep 2022
TreeMix: Compositional Constituency-based Data Augmentation for Natural Language Understanding Le Zhang Zichao Yang Diyi Yang 26 24 0 12 May 2022
DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling Lahari Poddar Peiyao Wang J. Reinspach 11 5 0 15 Apr 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 82 17 0 06 Feb 2022
Text and Code Embeddings by Contrastive Pre-Training Arvind Neelakantan Tao Xu Raul Puri Alec Radford Jesse Michael Han ... Tabarak Khan Toki Sherbakov Joanne Jang Peter Welinder Lilian Weng SSL AI4TS 213 421 0 24 Jan 2022
Efficient Contrastive Learning via Novel Data Augmentation and Curriculum Learning Seonghyeon Ye Jiseon Kim Alice H. Oh CLL VLM 24 21 0 10 Sep 2021
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach Víctor M. Sánchez-Cartagena M. Esplà-Gomis Juan Antonio Pérez-Ortiz Felipe Sánchez-Martínez 29 26 0 08 Sep 2021
A Survey on Data Augmentation for Text Classification Markus Bayer M. Kaufhold Christian A. Reuter 28 332 0 07 Jul 2021
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP Jiaao Chen Derek Tam Colin Raffel Mohit Bansal Diyi Yang 21 172 0 14 Jun 2021
Generate, Annotate, and Learn: NLP with Synthetic Text Xuanli He Islam Nassar J. Kiros Gholamreza Haffari Mohammad Norouzi 26 51 0 11 Jun 2021
ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer Yuanmeng Yan Rumei Li Sirui Wang Fuzheng Zhang Wei Yu Wu Weiran Xu SSL 35 546 0 25 May 2021
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 221 436 0 25 Sep 2019