mlsanityData to 14 Oct 2026

GeAR: Graph-enhanced Agent for Retrieval-augmented Generation

arXiv 2412.18431 ↗First posted 24 Dec 2024cs.CL cs.AI cs.IRcited by 17

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

Abstract (arXiv)

Retrieval-augmented Generation (RAG) relies on effective retrieval capabilities, yet traditional sparse and dense retrievers inherently struggle with multi-hop retrieval scenarios. In this paper, we introduce GeAR, a system that advances RAG performance through two key innovations: (i) an efficient graph expansion mechanism that augments any conventional base retriever, such as BM25, and (ii) an agent framework that incorporates the resulting graph-based retrieval into a multi-step retrieval framework. Our evaluation demonstrates GeAR's superior retrieval capabilities across three multi-hop question answering datasets. Notably, our system achieves state-of-the-art results with improvements exceeding 10% on the challenging MuSiQue dataset, while consuming fewer tokens and requiring fewer iterations than existing multi-step retrieval systems. The project page is available at https://gear-rag.github.io.

Key facts. Cited by 17 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 16 of its 32 references that are in the map. First posted on arXiv 24 Dec 2024.

Builds on

16 of 32 references.

Closest ancestors · 4

Same direction, newest first

  1. 2024KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation10 Sep
  2. 2024TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation17 Jun
  3. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarization24 Apr
  4. 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval31 Jan

Other references · 12

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  3. 2020Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Stepscited by 1,282
  4. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 923
  5. 2024LongRoPE: Extending LLM Context Window Beyond 2 Million Tokenscited by 313
  6. 2016Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Modelscited by 301
  7. 2023Knowledge Graph Prompting for Multi-Document Question Answeringcited by 152
  8. 2023Walking Down the Memory Maze: Beyond Context Limit through Interactive Readingcited by 133
  9. 2021Entailment as Few-Shot Learnercited by 123
  10. 2019Comparison of Diverse Decoding Methods from Conditional Language Modelscited by 78
  11. 2024GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Modelscited by 43
  12. 2024Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruningcited by 16

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 9; 2026: 8.

17 papers.

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  1. 2025Deep Research Agents: A Systematic Examination And Roadmapcited by 128
  2. 2026InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discoverycited by 27
  3. 2026SkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scalecited by 16
  4. 2026MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chainscited by 12
  5. 2025FlowSearch: Advancing deep research with dynamic structured knowledge flowcited by 10
  6. 2025Beyond Chunks and Graphs: Retrieval-Augmented Generation through Triplet-Driven Thinkingcited by 6
  7. 2025BELLE: A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answeringcited by 3
  8. 2025HetaRAG: Hybrid Deep Retrieval-Augmented Generation across Heterogeneous Data Storescited by 3
  9. 2025GraphSearch: An Agentic Deep Searching Workflow for Graph Retrieval-Augmented Generationcited by 3
  10. 2025Decomposing and Revising What Language Models Generatecited by 2
  11. 2025MARC: Multimodal and Multi-Task Agentic Retrieval-Augmented Generation for Cold-Start Recommender Systemcited by 1
  12. 2026G2-Reader: Dual Evolving Graphs for Multimodal Document QAcited by 1
5 more
  1. 2026VLM-DEWM: Dynamic External World Model for Verifiable and Resilient Vision-Language Planning in Manufacturingcited by 1
  2. 2025GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Frameworkcited by 0
  3. 2026EviReform: Evidence-Guided Query Reformulation for Multi-Hop Graph Retrievalcited by 0
  4. 2026Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Constructioncited by 0
  5. 2026Beyond Similarity through Zero-Token Geometric Graphs for Multi-Hop RAGcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Agent-Enhanced Heterogeneous Graph RAG for Academic Question Answering
  2. 2025Millions of GeAR-s: Extending GraphRAG to Millions of Documents
  3. 2026Agent-Orchestrated Adaptive RAG: A Comparative Study on Structured and Multi-Hop Retrieval
  4. 2025Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
  5. 2026LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation
  6. 2026Dissecting Agentic RAG: A Component Ablation for Multi-Hop QA with a Local 7B Model
  7. 2025Query-Centric Graph Retrieval Augmented Generation
  8. 2025HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented Generation