| Residential College | false |
| Status | 已發表Published |
| Intrinsic Model Weaknesses: How Priming Attacks Unveil Vulnerabilities in Large Language Models | |
Yuyi Huang1,2 ; Runzhe Zhan1; Derek F. Wong1 ; Lidia S. Chao1; Ailin Tao2
| |
| 2025-04 | |
| Conference Name | 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics |
| Source Publication | Findings of the Association for Computational Linguistics: NAACL 2025
 |
| Conference Date | 2025-04-29 |
| Conference Place | Albuquerque, New Mexico |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
| Affiliation | 1.NLP2CT Lab, Department of Computer and Information Science, University of Macau 2.The Second Affiliated Hospital, Guangdong Provincial Key Laboratory of Allergy and Clinical Immunology, Guangzhou Medical University |
| First Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Yuyi Huang,Runzhe Zhan,Derek F. Wong,et al. Intrinsic Model Weaknesses: How Priming Attacks Unveil Vulnerabilities in Large Language Models[C], 2025. |
| APA | Yuyi Huang., Runzhe Zhan., Derek F. Wong., Lidia S. Chao., & Ailin Tao (2025). Intrinsic Model Weaknesses: How Priming Attacks Unveil Vulnerabilities in Large Language Models. Findings of the Association for Computational Linguistics: NAACL 2025. |
| Files in This Item: | There are no files associated with this item. | |||||
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