mlsanityData to 14 Oct 2026

Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness

arXiv 2504.05163 ↗First posted 7 Apr 2025cs.AIcited by 7

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

Abstract (arXiv)

Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) is a technique that enhances Large Language Model (LLM) inference in tasks like Question Answering (QA) by retrieving relevant information from knowledge graphs (KGs). However, real-world KGs are often incomplete, meaning that essential information for answering questions may be missing. Existing benchmarks do not adequately capture the impact of KG incompleteness on KG-RAG performance. In this paper, we systematically evaluate KG-RAG methods under incomplete KGs by removing triples using different methods and analyzing the resulting effects. We demonstrate that KG-RAG methods are sensitive to KG incompleteness, highlighting the need for more robust approaches in realistic settings.

Key facts. Cited by 7 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 22 of its 31 references that are in the map. First posted on arXiv 7 Apr 2025.

Builds on

22 of 31 references.

Closest ancestors · 5

Same direction, newest first

  1. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models21 Jan
  2. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)31 Dec
  3. 2024Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation28 Oct
  4. 2024CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question Answering29 Sep
  5. 2024G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering12 Feb

Other references · 17

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2023Mistral 7Bcited by 3,164
  5. 2022Survey of Hallucination in Natural Language Generationcited by 2,075
  6. 2021Improving language models by retrieving from trillions of tokenscited by 1,293
  7. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,210
  8. 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 800
  9. 2023In-Context Retrieval-Augmented Language Modelscited by 702
  10. 2018The Web as a Knowledge-base for Answering Complex Questionscited by 410
  11. 2023Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoningcited by 328
  12. 2021Time-Aware Language Models as Temporal Knowledge Basescited by 296
5 more
  1. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 171
  2. 2023Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Taskscited by 59
  3. 2022Contextual Semantic Embeddings for Ontology Subsumption Predictioncited by 31
  4. 2025Supposedly Equivalent Facts That Aren't? Entity Frequency in Pre-training Induces Asymmetry in LLMscited by 6
  5. 2023Robust Knowledge Extraction from Large Language Models using Social Choice Theorycited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.

  1. 2025Large Language Models Meet Knowledge Graphs for Question Answering: Synthesis and Opportunitiescited by 31
  2. 2025ArgRAG: Explainable Retrieval Augmented Generation using Quantitative Bipolar Argumentationcited by 12
  3. 2025What Breaks Knowledge Graph based RAG? Benchmarking and Empirical Insights into Reasoning under Incomplete Knowledgecited by 9
  4. 2025GR-Agent: Adaptive Graph Reasoning Agent under Incomplete Knowledgecited by 2
  5. 2026Leveraging LLM-GNN Integration for Open-World Question Answering over Knowledge Graphscited by 2
  6. 2026AWM: Answerable Working Memory for Long-Document VQA Agentscited by 2
  7. 2026SCAIR: Schema-Conditioned Agentic Iterative Reasoning for Enterprise Knowledge Graphscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025KERAG: Knowledge-Enhanced Retrieval-Augmented Generation for Advanced Question Answering
  2. 2025Knowledge Graph-extended Retrieval Augmented Generation for Question Answering
  3. 2025Knowledge Graph-Guided Retrieval Augmented Generation
  4. 2025In-depth Analysis of Graph-based RAG in a Unified Framework
  5. 2024Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation
  6. 2025A Pilot Empirical Study on When and How to Use Knowledge Graphs as Retrieval Augmented Generation
  7. 2025Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey
  8. 2024SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation