GRASP: Graph Agentic Search over Propositions for Multi-hop Question Answering
Agentic retrieval improves multi-hop question answering by giving language models autonomy to iteratively gather evidence. Recent work augments these systems with knowledge graphs for structured traversal, but this combination introduces significant cost: expensive graph construction at index time and compounding token usage at inference time. We introduce Graph Agentic Search over Propositions (GRASP), an agentic system that simultaneously optimizes for high accuracy and minimal token usage in multi-hop question answering. Rather than executing a rigid, singular query, GRASP actively coordinates its retrieval strategy by decomposing multi-hop queries into dependency-aware plans. This ena...
| Authors | Stockton Jenkins, Ramya Korlakai Vinayak, Junjie Hu |
|---|---|
| Primary category | cs.MA |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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