A Context Aware Approach for Generating Natural Language Attacks

Authors

  • Rishabh Maheshwary International Institute of Information Technology, Hyderabad
  • Saket Maheshwary International Institute of Information Technology, Hyderabad
  • Vikram Pudi International Institute of Information Technology, Hyderabad

Keywords:

Adversarial Attacks, Adversarial Attacks And Robustness, NLP Applications, Natural Language Processing

Abstract

We study an important task of attacking natural language processing models in a black box setting. We propose an attack strategy that crafts semantically similar adversarial examples on text classification and entailment tasks. Our proposed attack finds candidate words by considering the information of both the original word and its surrounding context. It jointly leverages masked language modelling and next sentence prediction for context understanding. In comparison to attacks proposed in prior literature, we are able to generate high quality adversarial examples that do significantly better both in terms of success rate and word perturbation percentage.

Downloads

Published

2021-05-18

How to Cite

Maheshwary, R., Maheshwary, S., & Pudi, V. (2021). A Context Aware Approach for Generating Natural Language Attacks. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15839-15840. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17916

Issue

Section

AAAI Student Abstract and Poster Program