Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM Alignment

Large Language Models (LLMs) have seen widespread adoption due to their remarkable natural language capabilities. However, when deploying them in real-world settings, it is important to align LLMs to generate texts according to acceptable human standards. Methods such as Proximal Policy Optimization...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Feng, Qizhang, Siva Rajesh Kasa, Hyokun Yun, Choon Hui Teo, Sravan Babu Bodapati
Format:	Artikel
Sprache:	eng
Schlagworte:	Alignment Inference Large language models Optimization Privacy
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!