Retrieval-Augmented Generation for AI-Generated Content: A Survey

arXiv:2402.19473v1 Announce Type: new
Abstract: The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by advancements in model algorithms, scalable foundation model architectures, and the availability of ample high-quality datasets. While AIGC has achieved remarkable performance, it still faces challenges, such as the difficulty of maintaining up-to-date and long-tail knowledge, the risk of data leakage, and the high costs associated with training and inference. Retrieval-Augmented Generation (RAG) has recently emerged as a paradigm to address such challenges. In …

ai-generated content arxiv cs.cv generated retrieval retrieval-augmented survey type