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 …

arxiv cs.cr cs.db cs.lg data databases domain graph language language models large llms paradigm privacy private private data rag