Adversarial Training for Machine Reading Comprehension with Virtual Embeddings

Roberta: A robustly optimized BERT pretraining approach

Original

Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907

Earlier work this paper cites.

Huggingface’s transformers: State-of-the-art natural language processing

Original

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910

Earlier work this paper cites.

SMART: robust and efficient fine-tuning for pre-trained natural language models through principled regularized optimization

Original

Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, and Tuo Zhao. 2019 · 1911

Earlier work this paper cites.

Adversarial training for large neural language models

Original

Xiaodong Liu, Hao Cheng, Pengcheng He, Weizhu Chen, Yu Wang, Hoifung Poon, and Jianfeng Gao. 2020 · 2004

Earlier work this paper cites.

Adversarial training for commonsense inference

Original

Lis Pereira, Xiaodong Liu, Fei Cheng, Masayuki Asahara, and Ichiro Kobayashi. 2020 · 2005

Earlier work this paper cites.

Intriguing properties of neural networks

Original

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, and Rob Fergus. 2014 · 2014

Earlier work this paper cites.

Explaining and harnessing adversarial examples

Original

Ian Goodfellow, Jonathon Shlens, and Christian Szegedy. 2015 · 2015

Earlier work this paper cites.

SQuAD: 100,000+ questions for machine comprehension of text

Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016

Earlier work this paper cites.

RACE: Large-scale ReAding comprehension dataset from examinations

Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017

Cited alongside, same era.

Adversarial training methods for semi-supervised text classification

Takeru Miyato, Andrew M. Dai, and Ian J. Goodfellow. 2017 · 2017

Cited alongside, same era.

Adversarial training for relation extraction

Yi Wu, David Bamman, and Stuart Russell. 2017 · 2017

Cited alongside, same era.

Adversarial training for multi-context joint entity and relation extraction

Giannis Bekoulis, Johannes Deleu, Thomas Demeester, and Chris Develder. 2018 · 2018

Cited alongside, same era.

Bert: Pre-training of deep bidirectional transformers for language understanding

Original

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018

Cited alongside, same era.

Know what you don’t know: Unanswerable questions for SQuAD

Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018

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Exploring machine reading comprehension with explicit knowledge

Original

Chao Wang and Hui Jiang. 2018 · 2018

Later among the works it cites.

Hotpotqa: A dataset for diverse, explainable multi-hop question answering

Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018

Later among the works it cites.

Robust multilingual part-of-speech tagging via adversarial training

Michihiro Yasunaga, Jungo Kasai, and Dragomir Radev. 2018 · 2018

Later among the works it cites.

Is Graph Structure Necessary for Multi-hop Question Answering?

Nan Shao, Yiming Cui, Ting Liu, Shijin Wang, and Guoping Hu. 2020 · 2020

Later among the works it cites.