GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases
GRASP is a three-stage retrieval framework for semi-structured knowledge bases that combines graph planning with dense text retrieval. It uses an LLM to create a graph plan, executes it against a database, fuses the results with a text retriever based on the plan's risk level, and finally uses a fine-tuned reranker to reorder candidates. This hybrid approach significantly improves retrieval accuracy across benchmarks.