Deep Text Classification Can be Fooled

Deep Text Classification Can be Fooled

26 April 2017

Papers citing "Deep Text Classification Can be Fooled"

19 / 69 papers shown

Title
BAE: BERT-based Adversarial Examples for Text Classification Siddhant Garg Goutham Ramakrishnan AAML SILM 39 542 0 04 Apr 2020
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models Yankun Ren J. Lin Siliang Tang Jun Zhou Shuang Yang Yuan Qi Xiang Ren GAN AAML SILM 32 21 0 10 Mar 2020
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 Caiming Xiong SILM AAML 12 101 0 27 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 22 89 0 11 Feb 2020
Say What I Want: Towards the Dark Side of Neural Dialogue Models Haochen Liu Tyler Derr Zitao Liu Jiliang Tang 31 16 0 13 Sep 2019
Negative Training for Neural Dialogue Response Generation Tianxing He James R. Glass 30 59 0 06 Mar 2019
Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses Ananya B. Sai Mithun Das Gupta Mitesh M. Khapra Mukundhan Srinivasan 27 48 0 23 Feb 2019
Universal Rules for Fooling Deep Neural Networks based Text Classification Di Li Danilo Vasconcellos Vargas Kouichi Sakurai AAML 21 11 0 22 Jan 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 24 57 0 21 Jan 2019
TextBugger: Generating Adversarial Text Against Real-world Applications Jinfeng Li S. Ji Tianyu Du Bo Li Ting Wang SILM AAML 75 723 0 13 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 18 92 0 01 Dec 2018
Evading classifiers in discrete domains with provable optimality guarantees B. Kulynych Jamie Hayes N. Samarin Carmela Troncoso AAML 21 19 0 25 Oct 2018
Attack Graph Convolutional Networks by Adding Fake Nodes Xiaoyun Wang Minhao Cheng Joe Eaton Cho-Jui Hsieh S. F. Wu AAML GNN 33 78 0 25 Oct 2018
Detecting egregious responses in neural sequence-to-sequence models Tianxing He James R. Glass AAML 29 22 0 11 Sep 2018
Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models Tong Niu Joey Tianyi Zhou AAML 21 85 0 06 Sep 2018
Adversarial Texts with Gradient Methods Zhitao Gong Wenlu Wang Bohao Li D. Song Wei-Shinn Ku AAML 34 77 0 22 Jan 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers Ji Gao Jack Lanchantin M. Soffa Yanjun Qi AAML 47 707 0 13 Jan 2018
Towards Crafting Text Adversarial Samples Suranjana Samanta S. Mehta AAML 27 219 0 10 Jul 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 12 215 0 23 May 2017