Privacy-Preserving Neural Graph Databases

arXiv:2312.15591v3 Announce Type: replace-cross
Abstract: In the era of large language models (LLMs), efficient and accurate data retrieval has become increasingly crucial for the use of domain-specific or private data in the retrieval augmented generation (RAG). Neural graph databases (NGDBs) have emerged as a powerful paradigm that combines the strengths of graph databases (GDBs) and neural networks to enable efficient storage, retrieval, and analysis of graph-structured data which can be adaptively trained with LLMs. The usage of neural embedding storage …

abstract arxiv become cs.cr cs.db cs.lg data databases domain graph graph databases language language models large language large language models llms paradigm privacy private data rag retrieval retrieval augmented generation type