9 citations · 9 across the 4 of their papers we have counts for
4 papers
RoChBert: Towards Robust BERT Fine-tuning for Chinese
Zihan Zhang, Jinfeng Li, Ning Shi +6
Despite of the superb performance on a wide range of tasks, pre-trained language models (e.g., BERT) have been proved vulnerable to adversarial texts. In this paper, we present RoC…
Counterfactual Adversarial Learning with Representation Interpolation
Wei Wang, Boxin Wang, Ning Shi +4
Deep learning models exhibit a preference for statistical fitting over logical reasoning. Spurious correlations might be memorized when there exists statistical bias in training da…
Incorporating External POS Tagger for Punctuation Restoration
Ning Shi, Wei Wang, Boxin Wang +3
Punctuation restoration is an important post-processing step in automatic speech recognition. Among other kinds of external information, part-of-speech (POS) taggers provide inform…
Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation
Jinfeng Li, Tianyu Du, Xiangyu Liu +3
Despite that deep neural networks (DNNs) have achieved enormous success in many domains like natural language processing (NLP), they have also been proven to be vulnerable to malic…