ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP

Lu Yan, Zhuo Zhang 0002, Guanhong Tao 0001, Kaiyuan Zhang 0002, Xuan Chen, Guangyu Shen, Xiangyu Zhang. ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP. In Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine, editors, Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023. 2023. [doi]

Abstract

Abstract is missing.