Towards Robustness Against Natural Language Word Substitutions

28 July 2021

Papers citing "Towards Robustness Against Natural Language Word Substitutions"

21 / 71 papers shown

Title
Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions Marwan Omar Soohyeon Choi Daehun Nyang David A. Mohaisen 32 57 0 03 Jan 2022
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? Xinhsuai Dong Anh Tuan Luu Min-Bin Lin Shuicheng Yan Hanwang Zhang SILM AAML 20 55 0 22 Dec 2021
The King is Naked: on the Notion of Robustness for Natural Language Processing Emanuele La Malfa Marta Z. Kwiatkowska 20 28 0 13 Dec 2021
Detecting Textual Adversarial Examples through Randomized Substitution and Vote Xiaosen Wang Yifeng Xiong Kun He AAML 25 11 0 13 Sep 2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks Bin Zhu Zhaoquan Gu Le Wang Zhihong Tian AAML 36 8 0 13 Sep 2021
Towards Improving Adversarial Training of NLP Models Jin Yong Yoo Yanjun Qi AAML 10 123 0 01 Sep 2021
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding Lingyun Feng Jianwei Yu Deng Cai Songxiang Liu Haitao Zheng Yan Wang ELM 79 14 0 30 Aug 2021
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution Zongyi Li Jianhan Xu Jiehang Zeng Linyang Li Xiaoqing Zheng Qi Zhang Kai-Wei Chang Cho-Jui Hsieh AAML 8 74 0 29 Aug 2021
Evaluating the Robustness of Neural Language Models to Input Perturbations M. Moradi Matthias Samwald AAML 48 95 0 27 Aug 2021
On The State of Data In Computer Vision: Human Annotations Remain Indispensable for Developing Deep Learning Models Z. Emam Andrew Kondrich Sasha Harrison Felix Lau Yushi Wang Aerin Kim E. Branson VLM 30 11 0 31 Jul 2021
Self-Supervised Contrastive Learning with Adversarial Perturbations for Defending Word Substitution-based Attacks Zhao Meng Yihan Dong Mrinmaya Sachan Roger Wattenhofer AAML 66 10 0 15 Jul 2021
Certified Robustness to Text Adversarial Attacks by Randomized [MASK] Jiehang Zeng Xiaoqing Zheng Jianhan Xu Linyang Li Liping Yuan Xuanjing Huang AAML 26 67 0 08 May 2021
Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack Yixu Wang Jie Li Hong Liu Yan Wang Yongjian Wu Feiyue Huang Rongrong Ji AAML 25 34 0 03 May 2021
Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training Kuan-Hao Huang Wasi Uddin Ahmad Nanyun Peng Kai-Wei Chang AAML 97 34 0 17 Apr 2021
Certified Robustness to Programmable Transformations in LSTMs Yuhao Zhang Aws Albarghouthi Loris Dántoni AAML 17 22 0 15 Feb 2021
SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher Thai Le Noseong Park Dongwon Lee AAML 6 20 0 17 Nov 2020
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 183 291 0 03 Sep 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 250 915 0 21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 205 712 0 17 Apr 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 213 1,367 0 06 Jun 2016