Papers by Jiazhao Li
Defending against Insertion-based Textual Backdoor Attacks via Attribution (2023.findings-acl)
Copied to clipboard
| Challenge: | Textual backdoor attacks are vulnerable to backdoors and can be used to infect models trained on poisoned data. |
| Approach: | They propose an efficient attribution-based pipeline to defend against two insertion-based poisoning attacks, BadNL and InSent. |
| Outcome: | The proposed method can generalize sufficiently well in two common attack scenarios, which consistently improves previous methods. |
PharmMT: A Neural Machine Translation Approach to Simplify Prescription Directions (2020.findings-emnlp)
Copied to clipboard
| Challenge: | a novel machine translation-based approach to simplify prescription directions is proposed . the language used by physicians and health professionals includes medical jargon and implicit directives . |
| Approach: | They propose a machine translation-based approach to automatically and reliably simplify prescription directions into patient-friendly language. |
| Outcome: | The proposed system achieves a BLEU score of 60.27 over 530K prescriptions from a large mail-order pharmacy. |
ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger (2024.naacl-long)
Copied to clipboard
| Challenge: | Textual backdoor attacks are increasingly challenging to detect due to the use of advanced generative models such as GPT-4. |
| Approach: | They propose a framework that harnesses advanced generative models to execute stealthier backdoor attacks on text classifiers. |
| Outcome: | The proposed framework achieves state-of-the-art attack success rate of 97.35% over four sentiment classification tasks and four human cognition stealthiness tests. |