Enhancing adversarial robustness in Natural Language Inference using
explanations
Enhancing adversarial robustness in Natural Language Inference using
explanations
The surge of state-of-the-art Transformer-based models has undoubtedly pushed the limits of NLP model performance, excelling in a variety of tasks. We cast the spotlight on the underexplored task of Natural Language Inference (NLI), since models trained on popular well-suited datasets are susceptible to adversarial attacks, allowing subtle input interventions …