mlsanityData to 7 Oct 2026

HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction

arXiv 2408.04948 ↗First posted 9 Aug 2024cs.CL cs.LG q-fin.STcited by 92

On the map: Retrieval-augmented generation → Legal and financial RAG

Abstract (arXiv)

Extraction and interpretation of intricate information from unstructured text data arising in financial applications, such as earnings call transcripts, present substantial challenges to large language models (LLMs) even using the current best practices to use Retrieval Augmented Generation (RAG) (referred to as VectorRAG techniques which utilize vector databases for information retrieval) due to challenges such as domain specific terminology and complex formats of the documents. We introduce a novel approach based on a combination, called HybridRAG, of the Knowledge Graphs (KGs) based RAG techniques (called GraphRAG) and VectorRAG techniques to enhance question-answer (Q&A) systems for information extraction from financial documents that is shown to be capable of generating accurate and contextually relevant answers. Using experiments on a set of financial earning call transcripts documents which come in the form of Q&A format, and hence provide a natural set of pairs of ground-truth Q&As, we show that HybridRAG which retrieves context from both vector database and KG outperforms both traditional VectorRAG and GraphRAG individually when evaluated at both the retrieval and generation stages in terms of retrieval accuracy and answer generation. The proposed technique has applications beyond the financial domain

Key facts. Cited by 92 papers in the map (data through 7 Oct 2026). Placed in Legal and financial RAG, one of 15 directions in Retrieval-augmented generation. Builds on 20 of its 30 references that are in the map. First posted on arXiv 9 Aug 2024.

Builds on

20 of 30 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  4. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  5. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  6. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,411
  7. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  8. 2023BloombergGPT: A Large Language Model for Financecited by 923
  9. 2020A Survey on Knowledge Graphs: Representation, Acquisition and Applicationscited by 643
  10. 2020Knowledge Graphscited by 619
  11. 2021FinQA: A Dataset of Numerical Reasoning over Financial Datacited by 552
  12. 2021TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Financecited by 402
8 more
  1. 2023FinanceBench: A New Benchmark for Financial Question Answeringcited by 261
  2. 2020FinBERT: A Pretrained Language Model for Financial Communicationscited by 161
  3. 2023Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Surveycited by 134
  4. 2024Revolutionizing Finance with LLMs: An Overview of Applications and Insightscited by 88
  5. 2023A Comprehensive Survey on Automatic Knowledge Graph Constructioncited by 63
  6. 2024FinTextQA: A Dataset for Long-form Financial Question Answeringcited by 54
  7. 2024Financial Report Chunking for Effective Retrieval Augmented Generationcited by 46
  8. 2023Towards reducing hallucination in extracting information from financial reports using Large Language Modelscited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 11; 2025: 57; 2026: 24.

92 papers.

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  1. 2024Graph Retrieval-Augmented Generation: A Surveycited by 320
  2. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Modelscited by 85
  3. 2024KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generationcited by 67
  4. 2025KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAGcited by 29
  5. 2025Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Surveycited by 18
  6. 2025FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generationcited by 17
  7. 2025Graph RAG-Tool Fusioncited by 15
  8. 2025Tool-to-Agent Retrieval: Bridging Tools and Agents for Scalable LLM Multi-Agent Systemscited by 15
  9. 2025Knowledge Graph-based Retrieval-Augmented Generation for Schema Matchingcited by 13
  10. 2025AssertionForge: Enhancing Formal Verification Assertion Generation with Structured Representation of Specifications and RTLcited by 13
  11. 2025BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answeringcited by 10
  12. 2025Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrievalcited by 10
38 more
  1. 2025Cog-RAG: Cognitive-Inspired Dual-Hypergraph with Theme Alignment Retrieval-Augmented Generationcited by 9
  2. 2024Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Studycited by 8
  3. 2025FRAG: A Flexible Modular Framework for Retrieval-Augmented Generation based on Knowledge Graphscited by 8
  4. 2025KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracingcited by 8
  5. 2025DRAE: Dynamic Retrieval-Augmented Expert Networks for Lifelong Learning and Task Adaptation in Roboticscited by 8
  6. 2025DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoningcited by 8
  7. 2025Towards Temporal-Aware Multi-Modal Retrieval Augmented Generation in Financecited by 7
  8. 2025RoleRAG: Enhancing LLM Role-Playing via Graph Guided Retrievalcited by 7
  9. 2025TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Frameworkcited by 7
  10. 2024MEG: Medical Knowledge-Augmented Large Language Models for Question Answeringcited by 6
  11. 2024Multi-Document Financial Question Answering using LLMscited by 6
  12. 2025Retrieval Augmented Generation with Multi-Modal LLM Framework for Wireless Environmentscited by 5
  13. 2025SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routingcited by 5
  14. 2025OpsAgent: An Evolving Multi-agent System for Incident Management in Microservicescited by 5
  15. 2025TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checkingcited by 4
  16. 2025Hierarchical Retrieval with Evidence Curation for Open-Domain Financial Question Answering on Standardized Documentscited by 4
  17. 2025FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graphcited by 4
  18. 2025RAGTrace: Understanding and Refining Retrieval-Generation Dynamics in Retrieval-Augmented Generationcited by 4
  19. 2025Explainable Knowledge Graph Retrieval-Augmented Generation (KG-RAG) with KG-SMILEcited by 4
  20. 2025Agent-as-a-Graph: Knowledge Graph-Based Tool and Agent Retrieval for LLM Multi-Agent Systemscited by 4
  21. 2026RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routingcited by 4
  22. 2026Large Language Model-Assisted UAV Operations and Communications: A Multifaceted Survey and Tutorialcited by 4
  23. 2024FastRAG: Retrieval Augmented Generation for Semi-structured Datacited by 3
  24. 2024EQUATOR: A Deterministic Framework for Evaluating LLM Reasoning with Open-Ended Questions. # v1.0.0-betacited by 3
  25. 2025CORG: Generating Answers from Complex, Interrelated Contextscited by 3
  26. 2025NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answeringcited by 3
  27. 2025Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluationcited by 3
  28. 2025Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generationcited by 3
  29. 2025Right Answer at the Right Time - Temporal Retrieval-Augmented Generation via Graph Summarizationcited by 3
  30. 2026MARA: A Multimodal Adaptive Retrieval-Augmented Framework for Document Question Answeringcited by 3
  31. 2024Exploring Gen-AI applications in building research and industry: A reviewcited by 2
  32. 2025Optimizing open-domain question answering with graph-based retrieval augmented generationcited by 2
  33. 2025Ask2Loc: Learning to Locate Instructional Visual Answers by Asking Questionscited by 2
  34. 2025Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMscited by 2
  35. 2025XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generationcited by 2
  36. 2025Benchmarking Vector, Graph and Hybrid Retrieval Augmented Generation (RAG) Pipelines for Open Radio Access Networks (ORAN)cited by 2
  37. 2025Open-Source Agentic Hybrid RAG Framework for Scientific Literature Reviewcited by 2
  38. 2025DSRAG: A Domain-Specific Retrieval Framework Based on Document-derived Multimodal Knowledge Graphcited by 2

50 most cited of 92 All 92 (JSON)

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  1. 2025Rethinking Retrieval: From Traditional Retrieval Augmented Generation to Agentic and Non-Vector Reasoning Systems in the Financial Domain for Large Language Models
  2. 2025VeritasFi: An Adaptable, Multi-tiered RAG Framework for Multi-modal Financial Question Answering
  3. 2025Optimizing Retrieval Strategies for Financial Question Answering Documents in Retrieval-Augmented Generation Systems
  4. 2026Bypassing Document Ingestion: An MCP Approach to Financial Q&A
  5. 2024LightRAG: Simple and Fast Retrieval-Augmented Generation
  6. 2026Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study
  7. 2025RAG vs. GraphRAG: A Systematic Evaluation and Key Insights
  8. 2026Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents