28 citations · 58 across the 19 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2024
fairBERTs: Erasing Sensitive Information Through Semantic and Fairness-aware Perturbations
Jinfeng Li, Yuefeng Chen, Xiangyu Liu +3
Pre-trained language models (PLMs) have revolutionized both the natural language processing research and applications. However, stereotypical biases (e.g., gender and racial discri…
cs.CL2022
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…
cs.CL2021
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…