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GRASP framework advances SKB retrieval, boosting accuracy on STaRK benchmarks

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced GRASP, a novel three-stage framework for retrieving information from semi-structured knowledge bases (SKBs). This system integrates plan-based graph retrieval with a dense retriever and a reranker, significantly improving retrieval accuracy. GRASP demonstrated a substantial advancement on the STaRK benchmarks, increasing the average Hit@1 score from 62.0 to 73.9. AI

RANK_REASON The cluster contains an academic paper detailing a new retrieval framework and its benchmark performance.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

GRASP framework advances SKB retrieval, boosting accuracy on STaRK benchmarks

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Yicheng Tao, Yiqun Wang, Xiangchen Song, Xin Luo, Kai Liu, Jie Liu ·

    GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases

    arXiv:2605.30237v1 Announce Type: cross Abstract: Semi-structured knowledge bases (SKBs) embed textual documents in a typed graph of entities and relations, and underpin applications such as product search, academic paper search, and precision-medicine inquiries. Existing hybrid …

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Jie Liu ·

    GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases

    Semi-structured knowledge bases (SKBs) embed textual documents in a typed graph of entities and relations, and underpin applications such as product search, academic paper search, and precision-medicine inquiries. Existing hybrid retrieval systems on SKBs either use the graph onl…

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