5 citations · 7 across the 2 of their papers we have counts for
4 papers
TSCheater: Generating High-Quality Tibetan Adversarial Texts via Visual Similarity
Xi Cao, Quzong Gesang, Yuan Sun +2
Language models based on deep neural networks are vulnerable to textual adversarial attacks. While rich-resource languages like English are receiving focused attention, Tibetan, a…
Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script
Xi Cao, Dolma Dawa, Nuo Qun +1
The textual adversarial attack refers to an attack method in which the attacker adds imperceptible perturbations to the original texts by elaborate design so that the NLP (natural…
Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language Model
Xi Cao, Nuo Qun, Quzong Gesang +2
In social media, neural network models have been applied to hate speech detection, sentiment analysis, etc., but neural network models are susceptible to adversarial attacks. For i…
Human-in-the-Loop Generation of Adversarial Texts: A Case Study on Tibetan Script
Xi Cao, Yuan Sun, Jiajun Li +3
DNN-based language models excel across various NLP tasks but remain highly vulnerable to textual adversarial attacks. While adversarial text generation is crucial for NLP security,…