KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph
On the map: LLM reasoning → Knowledge- and tool-augmented reasoning
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Abstract (arXiv)
In this paper, we aim to improve the reasoning ability of large language models (LLMs) over knowledge graphs (KGs) to answer complex questions. Inspired by existing methods that design the interaction strategy between LLMs and KG, we propose an autonomous LLM-based agent framework, called KG-Agent, which enables a small LLM to actively make decisions until finishing the reasoning process over KGs. In KG-Agent, we integrate the LLM, multifunctional toolbox, KG-based executor, and knowledge memory, and develop an iteration mechanism that autonomously selects the tool then updates the memory for reasoning over KG. To guarantee the effectiveness, we leverage program language to formulate the multi-hop reasoning process over the KG, and synthesize a code-based instruction dataset to fine-tune the base LLM. Extensive experiments demonstrate that only using 10K samples for tuning LLaMA-7B can outperform state-of-the-art methods using larger LLMs or more data, on both in-domain and out-domain datasets. Our code and data will be publicly released.
Key facts. Cited by 93 papers in the map (data through 14 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 39 of its 49 references that are in the map. First posted on arXiv 17 Feb 2024.
Builds on
39 of 49 references.
Closest ancestors · 3
Same direction, newest first
- 2023ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph30 Dec
- 2023Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning2 Oct
- 2022UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph2 Dec
Other references · 36
- 2020Language Models are Few-Shot Learnerscited by 32,419
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- 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awarenesscited by 3,673
- 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
- 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,955
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
- 2023Code Llama: Open Foundation Models for Codecited by 2,139
- 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,745
- 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,694
- 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
24 more
- 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 719
- 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 668
- 2023MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Actioncited by 517
- 2018The Web as a Knowledge-base for Answering Complex Questionscited by 410
- 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 398
- 2023StructGPT: A General Framework for Large Language Model to Reason over Structured Datacited by 343
- 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
- 2016Key-Value Memory Networks for Directly Reading Documentscited by 223
- 2020Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Basescited by 171
- 2017Variational Reasoning for Question Answering with Knowledge Graphcited by 170
- 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 168
- 2021ExT5: Towards Extreme Multi-Task Scaling for Transfer Learningcited by 161
- 2023ChatDB: Augmenting LLMs with Databases as Their Symbolic Memorycited by 140
- 2021Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signalscited by 101
- 2022Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answeringcited by 93
- 2021RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answeringcited by 86
- 2020KQA Pro: A Dataset with Explicit Compositional Programs for Complex Question Answering over Knowledge Basecited by 78
- 2022TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Basescited by 59
- 2022Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environmentscited by 57
- 2021Complex Knowledge Base Question Answering: A Surveycited by 52
- 2023Do Large Language Models Know about Facts?cited by 51
- 2022ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answeringcited by 48
- 2022UniParser: A Unified Log Parser for Heterogeneous Log Datacited by 26
- 2023FC-KBQA: A Fine-to-Coarse Composition Framework for Knowledge Base Question Answeringcited by 21
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Citing papers per year: 2024: 22; 2025: 46; 2026: 25.
93 papers.
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