HippoRAG is a novel Retriever-Augmented Generation (RAG) framework inspired by human long-term memory, enabling Large Language Models (LLMs) to continuously integrate knowledge across external documents. Experiments demonstrate that HippoRAG can provide the capabilities of RAG systems, typically requiring expensive and high-latency iterative LLM pipelines, at a lower computational cost.