mlsanityData to 7 Oct 2026

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

arXiv 2605.30237 ↗First posted 28 May 2026cs.IR cs.CL cs.LGcited by 6

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Abstract (arXiv)

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 only for query expansion, mix textual and structural branches under a global weighting, or rely on fine-tuned graph-traversal generators. We present GRASP, a three-stage SKB retrieval framework unifying plan-based graph retrieval, plan-conditioned fusion with a dense retriever, and a fine-tuned reranker over the fused candidates. GRASP substantially advances the state of the art on every metric across the three STaRK benchmarks, lifting average Hit@1 from 62.0 to 73.9. Ablation and sensitivity studies further confirm the effectiveness and robustness of GRASP.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 40 references that are in the map. First posted on arXiv 28 May 2026.

Builds on

15 of 40 references.

References · 15

  1. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  2. 2021QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answeringcited by 386
  3. 2023Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graphcited by 235
  4. 2020Self-Alignment Pretraining for Biomedical Entity Representationscited by 233
  5. 2025AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agentscited by 82
  6. 2024HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Basescited by 26
  7. 2024Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrievalcited by 24
  8. 2026Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysiscited by 20
  9. 2025AutoPCR: Automated Phenotype Concept Recognition by Promptingcited by 10
  10. 2025Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge Basescited by 9
  11. 2024DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognitioncited by 5
  12. 2024Graphical Reasoning: LLM-based Semi-Open Relation Extractioncited by 4
3 more
  1. 2024HeteroMILE: a Multi-Level Graph Representation Learning Framework for Heterogeneous Graphscited by 2
  2. 2025Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledgecited by 2
  3. 2026SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognitioncited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architecturescited by 3
  2. 2026When Should Active RAG Retrieve? A Budget-Aware Evaluation of Utility, Calibration, and Costcited by 2
  3. 2026Dual Distribution Estimation for Zero-shot Noisy Test-Time Adaptation with VLMscited by 1
  4. 2026Toward User-Conditioned Evaluation of Personal LLM Agents under Temporal Interventionscited by 1
  5. 2026Evidence-Unit Fairness and the Limits of Query-Adaptive Sparse-Dense Fusion in Financial Document Retrievalcited by 1
  6. 2026Toward Workflow-Aware Benchmarking for Healthcare NLP Agentscited by 0