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cs.CR2024
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
Shenglai Zeng, Jiankun Zhang, Pengfei He +7
Retrieval-augmented generation (RAG) enhances the outputs of language models by integrating relevant information retrieved from external knowledge sources. However, when the retrie…
cs.CR2024
Copyright Protection in Generative AI: A Technical Perspective
Jie Ren, Han Xu, Pengfei He +10
Generative AI has witnessed rapid advancement in recent years, expanding their capabilities to create synthesized content such as text, images, audio, and code. The high fidelity a…
cs.CR2024
Data Poisoning for In-context Learning
Pengfei He, Han Xu, Yue Xing +3
In the domain of large language models (LLMs), in-context learning (ICL) has been recognized for its innovative ability to adapt to new tasks, relying on examples rather than retra…