mlsanityData to 7 Oct 2026

CommunityKG-RAG: Leveraging Community Structures in Knowledge Graphs for Advanced Retrieval-Augmented Generation in Fact-Checking

arXiv 2408.08535 ↗First posted 16 Aug 2024cs.CLcited by 11

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

Abstract (arXiv)

Despite advancements in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems, their effectiveness is often hindered by a lack of integration with entity relationships and community structures, limiting their ability to provide contextually rich and accurate information retrieval for fact-checking. We introduce CommunityKG-RAG (Community Knowledge Graph-Retrieval Augmented Generation), a novel zero-shot framework that integrates community structures within Knowledge Graphs (KGs) with RAG systems to enhance the fact-checking process. Capable of adapting to new domains and queries without additional training, CommunityKG-RAG utilizes the multi-hop nature of community structures within KGs to significantly improve the accuracy and relevance of information retrieval. Our experimental results demonstrate that CommunityKG-RAG outperforms traditional methods, representing a significant advancement in fact-checking by offering a robust, scalable, and efficient solution.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Placed in Knowledge-graph and structured-knowledge RAG, one of 15 directions in Retrieval-augmented generation. Builds on 23 of its 32 references that are in the map. First posted on arXiv 16 Aug 2024.

Builds on

23 of 32 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarization24 Apr

Other references · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  5. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  6. 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 788
  7. 2019K-BERT: Enabling Language Representation with Knowledge Graphcited by 303
  8. 2021ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generationcited by 258
  9. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  10. 2018Higher-order Coreference Resolution with Coarse-to-fine Inferencecited by 150
  11. 2024Seven Failure Points When Engineering a Retrieval Augmented Generation Systemcited by 138
  12. 2018Combining Fact Extraction and Verification with Neural Semantic Matching Networkscited by 120
10 more
  1. 2023Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answeringcited by 119
  2. 2019Fine-grained Fact Verification with Kernel Graph Attention Networkcited by 105
  3. 2022End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Modelscited by 105
  4. 2020CoLAKE: Contextualized Language and Knowledge Embeddingcited by 86
  5. 2023Self-Knowledge Guided Retrieval Augmentation for Large Language Modelscited by 69
  6. 2019BERT for Evidence Retrieval and Claim Verificationcited by 57
  7. 2023Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generationcited by 54
  8. 2023A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databasescited by 25
  9. 2023Assessing the Effectiveness of GPT-3 in Detecting False Political Statements: A Case Study on the LIAR Datasetcited by 7
  10. 2023Give Me More Details: Improving Fact-Checking with Latent Retrievalcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 9.

11 papers.

  1. 2025Graph-Augmented Reasoning: Evolving Step-by-Step Knowledge Graph Retrieval for LLM Reasoningcited by 8
  2. 2026Evaluating adaptive and generative AI-based feedback and recommendations in a knowledge-graph-integrated programming learning systemcited by 1
  3. 2025SLIDE: Sliding Localized Information for Document Extractioncited by 0
  4. 2026LPCAN: Lightweight Pyramid Cross-Attention Network for Rail Surface Defect Detection Using RGB-D Datacited by 0
  5. 2026Knowledge-Embedded and Hypernetwork-Guided Few-Shot Substation Meter Defect Image Generation Methodcited by 0
  6. 2026MA-LipNet: Multi-Dimensional Attention Networks for Robust Lipreadingcited by 0
  7. 2026The Diffusion Duet: Harmonizing Dual Channels with Wavelet Suppression for Image Separationcited by 0
  8. 2026Detecting Deepfakes with Multivariate Soft Blending and CLIP-based Image-Text Alignmentcited by 0
  9. 2026Efficient Image Super-Resolution with Multi-Scale Spatial Adaptive Attention Networkscited by 0
  10. 2026A Deformable Attention-Based Detection Transformer with Cross-Scale Feature Fusion for Industrial Coil Spring Inspectioncited by 0
  11. 2026RuleMem: Active Rule Memory for Long-Term Conversational Agentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
  2. 2024Face the Facts! Evaluating RAG-based Pipelines for Professional Fact-Checking
  3. 2025TruthfulRAG: Resolving Factual-level Conflicts in Retrieval-Augmented Generation with Knowledge Graphs
  4. 2025Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievals
  5. 2024SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation
  6. 2026Benchmarking Large Language Models for Knowledge Graph Validation
  7. 2026HG-RAG: Hierarchy-Guided Retrieval-Augmented Generation for Structured Knowledge Graphs
  8. 2026DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation