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Transfer learning with large pretrained transformer-based language models like BERT has become a dominating approach for most NLP tasks.
Electra: Pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V Le, and Christopher D Manning. 2020 · 2003
Earlier work this paper cites.
Adv-bert: Bert is not robust on misspellings! generating nature adversarial samples on bert
Lichao Sun, Kazuma Hashimoto, Wenpeng Yin, Akari Asai, Jia Li, Philip Yu, and Caiming Xiong. 2020 · 2003
Earlier work this paper cites.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A Smith. 2020 · 2004
Earlier work this paper cites.
Bert-attack: Adversarial attack against bert using bert
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2004
Earlier work this paper cites.
Adapterfusion: Non-destructive task composition for transfer learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych. 2020a · 2005
Earlier work this paper cites.
Deepfool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard. 2016 · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks
Jason Phang, Thibault Févry, and Samuel R Bowman. 2018 · 2018
Earlier work this paper cites.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 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. 2019 · 2019
Cited alongside, same era.
Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
Cited alongside, same era.
Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 2019
Cited alongside, same era.
Mixout: Effective regularization to finetune large-scale pretrained language models
Cheolhyoung Lee, Kyunghyun Cho, and Wanmo Kang. 2019 · 2019
Cited alongside, same era.
Robust neural machine translation with joint textual and phonetic embedding
Hairong Liu, Mingbo Ma, Liang Huang, Hao Xiong, and Zhongjun He. 2019 · 2019
Cited alongside, same era.
Pre-training via paraphrasing
Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, Armen Aghajanyan, Sida Wang, and Luke Zettlemoyer. 2020 · 2020
Later among the works it cites.
On the stability of fine-tuning bert: Misconceptions, explanations, and strong baselines
Marius Mosbach, Maksym Andriushchenko, and Dietrich Klakow. 2020 · 2020
Later among the works it cites.
BERTweet: A pre-trained language model for English Tweets
Dat Quoc Nguyen, Thanh Vu, and Anh Tuan Nguyen. 2020 · 2020
Later among the works it cites.
Adapterhub: A framework for adapting transformers
Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vulić, Sebastian Ruder, Kyunghyun Cho, and Iryna Gurevych. 2020b · 2020
Later among the works it cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Later among the works it cites.
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To tune or not to tune? adapting pretrained representations to diverse tasks
Matthew E Peters, Sebastian Ruder, and Noah A Smith. 2019 · 2019
Cited alongside, same era.
Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
Cited alongside, same era.
Neural transfer learning for natural language processing
Sebastian Ruder. 2019 · 2019
Cited alongside, same era.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
Cited alongside, same era.
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.
On the effectiveness of adapter-based tuning for pretrained language model adaptation
Ruidan He, Linlin Liu, Hai Ye, Qingyu Tan, Bosheng Ding, Liying Cheng, Jia-Wei Low, Lidong Bing, and Luo Si. 2021 · 2021
Closest in time.
SCRIPT: Self-critic PreTraining of transformers
Erik Nijkamp, Bo Pang, Ying Nian Wu, and Caiming Xiong. 2021 · 2021
Closest in time.