mlsanityData to 14 Oct 2026

DeepRAG: Integrating Hierarchical Reasoning and Process Supervision for Biomedical Multi-Hop QA

arXiv 2506.00671 ↗First posted 31 May 2025cs.CLcited by 2

On the map: Retrieval-augmented generation → Knowledge-graph and structured-knowledge RAG

Abstract (arXiv)

We propose DeepRAG, a novel framework that integrates DeepSeek hierarchical question decomposition capabilities with RAG Gym unified retrieval-augmented generation optimization using process level supervision. Targeting the challenging MedHopQA biomedical question answering task, DeepRAG systematically decomposes complex queries into precise sub-queries and employs concept level reward signals informed by the UMLS ontology to enhance biomedical accuracy. Preliminary evaluations on the MedHopQA dataset indicate that DeepRAG significantly outperforms baseline models, including standalone DeepSeek and RAG Gym, achieving notable improvements in both Exact Match and concept level accuracy.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Knowledge-graph and structured-knowledge RAG, one of 15 directions in Retrieval-augmented generation. Builds on 13 of its 16 references that are in the map. First posted on arXiv 31 May 2025.

Builds on

13 of 16 references.

References · 13

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  3. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  4. 2024ComposerX: Multi-Agent Symbolic Music Composition with LLMscited by 42
  5. 2025GraphRAG under Firecited by 24
  6. 2024RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Textscited by 23
  7. 2024Enhance Image-to-Image Generation with LLaVA-generated Promptscited by 20
  8. 2024Advances in APPFL: A Comprehensive and Extensible Federated Learning Frameworkcited by 19
  9. 2024A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Modelcited by 12
  10. 2025Scalability Optimization in Cloud-Based AI Inference Services: Strategies for Real-Time Load Balancing and Automated Scalingcited by 10
  11. 2025Data Augmentation Through Random Style Replacementcited by 9
  12. 2025Optimized Path Planning for Logistics Robots Using Ant Colony Algorithm under Multiple Constraintscited by 7
1 more
  1. 2024Scam Detection for Ethereum Smart Contracts: Leveraging Graph Representation Learning for Secure Blockchaincited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Transforming Questions and Documents for Semantically Aligned Retrieval-Augmented Generationcited by 1
  2. 2026Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answeringcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026UETQuintet at BioCreative IX -- MedHopQA: Enhancing Biomedical QA with Selective Multi-hop Reasoning and Contextual Retrieval
  2. 2025DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering
  3. 2025MedBioRAG: Semantic Search and Retrieval-Augmented Generation with Large Language Models for Medical and Biological QA
  4. 2026A Matryoshka Hierarchical RAG for Efficient Multi-Hop Question Answering
  5. 2025RAG-BioQA: A Retrieval-Augmented Generation Framework for Long-Form Biomedical Question Answering
  6. 2025StepChain GraphRAG: Reasoning Over Knowledge Graphs for Multi-Hop Question Answering
  7. 2026AdaPath: Query-Adaptive Path-Finding via Path-Bank for Multi-Hop Implicit Biomedical KGQA
  8. 2026Beyond Reachability: A Relation-Semantic Reasoning Framework for Biomedical Multi-hop QA