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Latest papers with code

Generating Natural Language Attacks in a Hard Label Black Box Setting

29 Dec 2020RishabhMaheshwary/hard-label-attack

Our proposed attack strategy leverages population-based optimization algorithm to craft plausible and semantically similar adversarial examples by observing only the top label predicted by the target model.

ADVERSARIAL TEXT SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY TEXT CLASSIFICATION

13
29 Dec 2020

Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples

9 Sep 2020QData/TextAttack

We study the behavior of several black-box search algorithms used for generating adversarial examples for natural language processing (NLP) tasks.

ADVERSARIAL TEXT DATA AUGMENTATION

1,426
09 Sep 2020

Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild

3 Sep 2020weijiawu/SyntoReal_STD

To address the severe domain distribution mismatch, we propose a synthetic-to-real domain adaptation method for scene text detection, which transfers knowledge from synthetic data (source domain) to real data (target domain).

ADVERSARIAL TEXT SCENE TEXT SCENE TEXT DETECTION UNSUPERVISED DOMAIN ADAPTATION

16
03 Sep 2020

End-to-End Adversarial Text-to-Speech

ICLR 2021 yanggeng1995/EATS

Modern text-to-speech synthesis pipelines typically involve multiple processing stages, each of which is designed or learnt independently from the rest.

ADVERSARIAL TEXT DYNAMIC TIME WARPING SPEECH SYNTHESIS TEXT-TO-SPEECH SYNTHESIS

98
05 Jun 2020

TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP

29 Apr 2020QData/TextAttack

TextAttack also includes data augmentation and adversarial training modules for using components of adversarial attacks to improve model accuracy and robustness.

ADVERSARIAL ATTACK ADVERSARIAL TEXT DATA AUGMENTATION LEXICAL ENTAILMENT MACHINE TRANSLATION TEXT CLASSIFICATION

1,426
29 Apr 2020

BAE: BERT-based Adversarial Examples for Text Classification

EMNLP 2020 QData/TextAttack

Modern text classification models are susceptible to adversarial examples, perturbed versions of the original text indiscernible by humans which get misclassified by the model.

ADVERSARIAL ATTACK ADVERSARIAL TEXT CLASSIFICATION TEXT CLASSIFICATION

1,428
04 Apr 2020

T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack

EMNLP 2020 AI-secure/T3

In particular, we propose a tree-based autoencoder to embed the discrete text data into a continuous representation space, upon which we optimize the adversarial perturbation.

ADVERSARIAL ATTACK ADVERSARIAL TEXT QUESTION ANSWERING SENTIMENT ANALYSIS TEXT GENERATION

22
22 Dec 2019

Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples

21 Aug 2019Top-Ranger/text_adversarial_attack

Adversarial examples are artificially modified input samples which lead to misclassifications, while not being detectable by humans.

ADVERSARIAL TEXT CLASSIFICATION IMAGE CLASSIFICATION TEXT CLASSIFICATION

2
21 Aug 2019

Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment

27 Jul 2019jind11/TextFooler

Machine learning algorithms are often vulnerable to adversarial examples that have imperceptible alterations from the original counterparts but can fool the state-of-the-art models.

ADVERSARIAL TEXT CLASSIFICATION NATURAL LANGUAGE INFERENCE TEXT CLASSIFICATION

316
27 Jul 2019

TextBugger: Generating Adversarial Text Against Real-world Applications

13 Dec 2018CatherineWong/dancin_seq2seq

Deep Learning-based Text Understanding (DLTU) is the backbone technique behind various applications, including question answering, machine translation, and text classification.

ADVERSARIAL TEXT MACHINE TRANSLATION QUESTION ANSWERING SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS TEXT CLASSIFICATION

22
13 Dec 2018