mlsanityData to 14 Oct 2026

AGENTiGraph: A Multi-Agent Knowledge Graph Framework for Interactive, Domain-Specific LLM Chatbots

arXiv 2508.02999 ↗First posted 5 Aug 2025cs.AI cs.CLcited by 10

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

AGENTiGraph is a user-friendly, agent-driven system that enables intuitive interaction and management of domain-specific data through the manipulation of knowledge graphs in natural language. It gives non-technical users a complete, visual solution to incrementally build and refine their knowledge bases, allowing multi-round dialogues and dynamic updates without specialized query languages. The flexible design of AGENTiGraph, including intent classification, task planning, and automatic knowledge integration, ensures seamless reasoning between diverse tasks. Evaluated on a 3,500-query benchmark within an educational scenario, the system outperforms strong zero-shot baselines (achieving 95.12% classification accuracy, 90.45% execution success), indicating potential scalability to compliance-critical or multi-step queries in legal and medical domains, e.g., incorporating new statutes or research on the fly. Our open-source demo offers a powerful new paradigm for multi-turn enterprise knowledge management that bridges LLMs and structured graphs.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 21 of its 36 references that are in the map. First posted on arXiv 5 Aug 2025.

Builds on

21 of 36 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  4. 2020A Survey on Knowledge Graphs: Representation, Acquisition and Applicationscited by 643
  5. 2019Generalizing from a Few Examples: A Survey on Few-Shot Learningcited by 463
  6. 2024Knowledge Conflicts for LLMs: A Surveycited by 283
  7. 2023ToolQA: A Dataset for LLM Question Answering with External Toolscited by 274
  8. 2015A Review of Relational Machine Learning for Knowledge Graphscited by 265
  9. 2016End-to-End Relation Extraction using LSTMs on Sequences and Tree Structurescited by 161
  10. 2023Factuality Challenges in the Era of Large Language Modelscited by 126
  11. 2024KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniquescited by 37
  12. 2022Modern Baselines for SPARQL Semantic Parsingcited by 34
9 more
  1. 2023DetermLR: Augmenting LLM-based Logical Reasoning from Indeterminacy to Determinacycited by 34
  2. 2024LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphscited by 22
  3. 2024Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Biascited by 20
  4. 2022Natural Language Interfaces to Datacited by 14
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  9. 2020Application of Pre-training Models in Named Entity Recognitioncited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 8.

10 papers.

  1. 2026InfiAgent: An Infinite-Horizon Framework for General-Purpose Autonomous Agentscited by 10
  2. 2025InfiAgent: Self-Evolving Pyramid Agent Framework for Infinite Scenarioscited by 4
  3. 2025Deterministic Legal Agents: A Canonical Primitive API for Auditable Reasoning over Temporal Knowledge Graphscited by 2
  4. 2026Cost and Accuracy of Long-Term Memory in Distributed Multi-Agent Systems Based on Large Language Modelscited by 2
  5. 2026MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphscited by 2
  6. 2026LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrievalcited by 0
  7. 2026LLMs+Graphs: Toward Graph-Native, Synergistic AI Systemscited by 0
  8. 2026Trust-Aware Multi-Agent Traceability: Confidence-Calibrated Knowledge Graphs for Consistent Software Artifact Managementcited by 0
  9. 2026Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generationcited by 0
  10. 2026Curriculum Brain: Constructing Curriculum Knowledge Graphs as a Substrate for Cognitive Diagnosiscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024AGENTiGraph: An Interactive Knowledge Graph Platform for LLM-based Chatbots Utilizing Private Data
  2. 2025AMAS: Adaptively Determining Communication Topology for LLM-based Multi-Agent System
  3. 2024AgentKit: Structured LLM Reasoning with Dynamic Graphs
  4. 2026Graph-of-Agents: A Graph-based Framework for Multi-Agent LLM Collaboration
  5. 2025KnowThyself: An Agentic Assistant for LLM Interpretability
  6. 2025LLM-Based Data Science Agents: A Survey of Capabilities, Challenges, and Future Directions
  7. 2026G2CP: A Graph-Grounded Communication Protocol for Verifiable and Efficient Multi-Agent Reasoning
  8. 2024AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents