32 citations · 62 across the 4 of their papers we have counts for
4 papers
DiffuseDef: Improved Robustness to Adversarial Attacks via Iterative Denoising
Zhenhao Li, Huichi Zhou, Marek Rei +1
Pretrained language models have significantly advanced performance across various natural language processing tasks. However, adversarial attacks continue to pose a critical challe…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Visual Cues and Error Correction for Translation Robustness
Zhenhao Li, Marek Rei, Lucia Specia
Neural Machine Translation models are sensitive to noise in the input texts, such as misspelled words and ungrammatical constructions. Existing robustness techniques generally fail…
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation
Zhenhao Li, Lucia Specia
Neural Machine Translation (NMT) models have been proved strong when translating clean texts, but they are very sensitive to noise in the input. Improving NMT models robustness can…