2 code implementations • 8 Feb 2024 • Guo Lin, Wenyue Hua, Yongfeng Zhang
While these models offer substantial benefits in terms of accessibility and functionality, they also introduce significant privacy concerns: the transmission and storage of user data in cloud infrastructures pose substantial risks of data breaches and unauthorized access to sensitive information; even if the transmission and storage of data is encrypted, the LLM service provider itself still knows the real contents of the data, preventing individuals or entities from confidently using such LLM services.
no code implementations • 8 May 2023 • Guo Lin, Yongfeng Zhang
This study investigates the feasibility of developing an Artificial General Recommender (AGR), facilitated by recent advancements in Large Language Models (LLMs).