7 citations · 13 across the 5 of their papers we have counts for
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cs.CL2022★ 4 cited
A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement
Yuting Yang, Pei Huang, Juan Cao +5
Recent years have seen the wide application of NLP models in crucial areas such as finance, medical treatment, and news media, raising concerns of the model robustness and vulnerab…
cs.CL2022★ 1 cited
Quantifying Robustness to Adversarial Word Substitutions
Yuting Yang, Pei Huang, FeiFei Ma +4
Deep-learning-based NLP models are found to be vulnerable to word substitution perturbations. Before they are widely adopted, the fundamental issues of robustness need to be addres…
cs.CL2022★ 7 cited
A Dual Prompt Learning Framework for Few-Shot Dialogue State Tracking
Yuting Yang, Wenqiang Lei, Pei Huang +3
Dialogue state tracking (DST) module is an important component for task-oriented dialog systems to understand users' goals and needs. Collecting dialogue state labels including slo…