LinearRAG provides a relation-free graph construction approach for retrieval-augmented generation on large-scale corpora. It aims to make GraphRAG more efficient by removing the need for LLM calls during graph construction, thereby reducing token costs while maintaining retrieval quality. The project includes benchmark code and is associated with other RAG-related research works from the same group.