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Data augmentation is a widely employed technique to alleviate the problem of data scarcity.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
Earlier work this paper cites.
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick and Hinrich Schütze. 2021 · 2001
Earlier work this paper cites.
Data Augmentation using Pre-trained Transformer Models
Varun Kumar, Ashutosh Choudhary, and Eunah Cho. 2021 · 2003
Earlier work this paper cites.
Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005
Earlier work this paper cites.
Improving Neural Machine Translation Models with Monolingual Data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, Maël Primet, and Joseph Dureau. 2018 · 2018
Earlier work this paper cites.
Deep Contextualized Word Representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Earlier work this paper cites.
Conditional BERT Contextual Augmentation
Xing Wu, Shangwen Lv, Liangjun Zang, Jizhong Han, and Songlin Hu. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2019
Cited alongside, same era.
A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification
Varun Kumar, Hadrien Glaude, Cyprien de Lichy, and Wlliam Campbell. 2019 · 2019
Cited alongside, same era.
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
Stefan Larson, Anish Mahendran, Joseph J. Peper, Christopher Clarke, Andrew Lee, Parker Hill, Jonathan K. Kummerfeld, Kevin Leach, Michael A. Laurenzano, Lingjia Tang, and Jason Mars. 2019 · 2019
Cited alongside, same era.
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
Jason Wei and Kai Zou. 2019 · 2019
Cited alongside, same era.
Benchmarking natural language understanding services for building conversational agents
Pawel Swietojanski Xingkun Liu, Arash Eshghi and Verena Rieser. 2019 · 2019
How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
Later among the works it cites.
Neural Data Augmentation via Example Extrapolation
Kenton Lee, Kelvin Guu, Luheng He, Tim Dozat, and Hyung Won Chung. 2021 · 2021
Later among the works it cites.
ConvFiT: Conversational fine-tuning of pretrained language models
Ivan Vulić, Pei-Hao Su, Samuel Coope, Daniela Gerz, Paweł Budzianowski, Iñigo Casanueva, Nikola Mrkšić, and Tsung-Hsien Wen. 2021 · 2021
Later among the works it cites.
GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
Later among the works it cites.
Want To Reduce Labeling Cost? GPT-3 Can Help
Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu, and Michael Zeng. 2021 · 2021
Later among the works it cites.
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Cited alongside, same era.
Do Not Have Enough Data? Deep Learning to the Rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, Naama Tepper, and Naama Zwerdling. 2020 · 2020
Cited alongside, same era.
Efficient intent detection with dual sentence encoders
Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, Matthew Henderson, and Ivan Vulić. 2020 · 2020
Cited alongside, same era.
GPT3Mix: Leveraging large-scale language models for text augmentation
Kang Min Yoo, Dongju Park, Jaewook Kang, Sang-Woo Lee, and Woomyoung Park. 2021 · 2021
Later among the works it cites.
Generating training data with language models: Towards zero-shot language understanding
Yu Meng, Jiaxin Huang, Yu Zhang, and Jiawei Han. 2022 · 2022
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