This repository contains a list of resources, including papers, tools, and data sources on the Retrieval-Augmented Generation with Graphs, we categorize them based on their applied graph domain.
We will try to make this list updated. If you found any error or any missed paper, please don't hesitate to open issues or pull requests.
Note: 🔥 indicates the paper is extensively cited (e.g., > 80 citations). The code is provided in get_hot.py.
- [Databricks] Improving Retrieval and RAG with Embedding Model Finetuning [Blog]
- [Github Repo] Advanced RAG Techniques: Elevating Your Retrieval-Augmented Generation Systems [code]
- [arXiv 24] Graph Retrieval-Augmented Generation: A Survey [paper]
- [arXiv 24] Evaluation of Retrieval-Augmented Generation: A Survey [paper]
- [NeurIPS 24] CRAG -- Comprehensive RAG Benchmark [paper][code]
- [arXiv 24] RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems [paper][code]
- [NeurIPS 24] STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases [paper] [code]
- [ACL 24] Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs [paper] [code]
- [arXiv 25] A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models [paper][code]
- [arXiv 25] RAG vs. GraphRAG: A Systematic Evaluation and Key Insights [paper]
- [arXiv 25] Graph Data Management and Graph Machine Learning: Synergies and Opportunities
- [NAACL 21] QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering [paper] [code]
- [ICLR 22] GreaseLM: Graph REASoning Enhanced Language Models for Question Answering [paper] [code]
- [NeurIPS 22] Deep bidirectional language-knowledge graph pretraining [paper] [code]
- [ICLR 24] Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph [paper] [code]
- [arXiv 23] Think and retrieval: A hypothesis knowledge graph enhanced medical large language models [paper]
- [arXiv 24] Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge [paper]
- [EMNLP 22] Empowering Language Models with Knowledge Graph Reasoning for Open-Domain Question Answering [paper]
- [ACL 22] Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering [paper] [code]
- [arXiv 24] KG-RAG: Bridging the Gap Between Knowledge and Creativity [paper] [code]
- [ICLR 24] Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning [paper] [code]
- [CIS 24] KnowledgeNavigator: Leveraging Large Language Models for Enhanced Reasoning over Knowledge Graph [paper]
- [IJCKG 23] Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering [paper] [code]
- [arXiv 24] Reasoning on Efficient Knowledge Paths: Knowledge Graph Guides Large Language Model for Domain Question Answering [paper]
- [EMNLP 19] PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text [paper]
- [CIKM 23] A Retrieve-and-Read Framework for Knowledge Graph Link Prediction [paper] [code]
- [SIGIR-GenIR 24] Mitigating Hallucinations in Large Language Models via Self-Refinement-Enhanced Knowledge Retrieval [paper]
- [AAAI 24] Graph neural prompting with large language models [paper] [code]
- [EMNLP 23] StructGPT: A General Framework for Large Language Model to Reason over Structured Data [paper] [code]
- [NeurIPS-CaLM 24] Causal Reasoning in Large Language Models: A Knowledge Graph Approach [paper]
- [AACL 22] Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph [paper]
- [ACL 23] Mvp-tuning: Multi-view knowledge retrieval with prompt tuning for commonsense reasoning [paper] [code]
- [arXiv 24] Large Language Models Can Better Understand Knowledge Graphs Than We Thought [paper]
- [ACL 24] ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models [paper] [code]
- [arXiv 23] keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM [paper]
- [arXiv 24] GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning [paper] [code]
- [arXiv 24] Explore then Determine: A GNN-LLM Synergy Framework for Reasoning over Knowledge Graph [paper]
- [NeurIPS 24] STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases [paper] [code]
- [EMNLP 20] Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering [paper] [code]
- [ACL 24] REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation [paper] [code]
- [ACL 23] KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models [paper] [code]
- [ACL 24] MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models [paper] [code]
- [EMNLP 24] DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature [paper] [code]
- [arXiv 24] UniOQA: A Unified Framework for Knowledge Graph Question Answering with Large Language Models [paper]
- [ACL 24] KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques [paper]
- [arXiv 24] Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation [paper] [code]
- [arXiv 23] KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases [paper]
- [arXiv 24] KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph [paper]
- [arXiv 24] KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents [paper] [code]
- [arXiv 24] Complex Logical Reasoning over Knowledge Graphs using Large Language Models [paper] [code]
- [WWW 23] GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering [paper]
- [NAACL 24] GenTKG: Generative Forecasting on Temporal Knowledge Graph with Large Language Models [paper] [code]
- [ACL 24] Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models [paper]
- [arXiv 24] EMERGE: Integrating RAG for Improved Multimodal EHR Predictive Modeling [paper]
- [arXiv 24] REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Models [paper]
- [EMNLP 23] KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models [paper] [code]
- [ArXiv 25] GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation [paper] [code]
- [ArXiv 24] Multi-hop Question Answering under Temporal Knowledge Editing [paper]
- [ICCL 25] GraphRAG: Leveraging Graph-Based Efficiency to Minimize Hallucinations in LLM-Driven RAG for Finance Data [paper]
- [ArXiv 25] Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation [paper]
- [ArXiv 25] PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths [paper][code]
- [CoNLL 17] Graph-based Neural Multi-Document Summarization [paper]
- [ACL 20] Heterogeneous Graph Neural Networks for Extractive Document Summarization [paper] [code]
- [ACL 20] Leveraging Graph to Improve Abstractive Multi-Document Summarization [paper] [code]
- [ACL 23] Contrastive Hierarchical Discourse Graph for Scientific Document Summarization [paper]
- [NAACL 24] Hierarchical Attention Graph for Scientific Document Summarization in Global and Local Level [paper] [code]
- [COLING 22] GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization [paper] [code]
- [EACL 23] Enhancing Multi-Document Summarization with Cross-Document Graph-based Information Extraction [paper] [code]
- [Information 18] An Integrated Graph Model for Document Summarization [paper]
- [AAAI 23] Compressed heterogeneous graph for abstractive multi-document summarization [paper] [code]
- [EMNLP 21] SgSum:Transforming Multi-document Summarization into Sub-graph Selection [paper] [code]
- [IP&M 24] From coarse to fine: Enhancing multi-document summarization with multi-granularity relationship-based extractor [paper]
- [arXiv 24] From Local to Global: A Graph RAG Approach to Query-Focused Summarization [paper] [code]
- [CIKM 24] Augmenting Textual Generation via Topology Aware Retrieval [paper] [code]
- [ICML 24] Llaga: Large language and graph assistant [paper] [code]
- [arXiv 24] Gofa: A generative one-for-all model for joint graph language modeling [paper] [code]
- [ACL 23] Don't Forget to Connect! Improving RAG with Graph-based Reranking [paper] [code]
- [WWW 21] Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval [paper] [code]
- [EMNLP 18] Graph Convolution over Pruned Dependency Trees Improves Relation Extraction [paper] [code]
- [arXiv 18] Matching Long Text Documents via Graph Convolutional Networks [paper]
- [arXiv 24] LightRAG: Simple and Fast Retrieval-Augmented Generation [paper] [code]
- [ACL 20] Every document owns its structure: Inductive text classification via graph neural networks [paper] [code]
- [IJCAI-19] Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification [paper] [code]
- [EMNLP 20] Text graph transformer for document classification [paper]
- [MVA 22] Graph neural networks in node classification: survey and evaluation [paper]
- [EMNLP 22] Capturing Global Structural Information in Long Document Question Answering with Compressive Graph Selector Network [paper] [code]
- [SIGIR 23] DocGraphLM: Documental Graph Language Model for Information Extraction [paper]
- [arXiv 24] G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering [paper] [code]
- [AAAI 24] Knowledge graph prompting for multi-document question answering [paper] [code]
- [EMNLP 20] Hierarchical Graph Network for Multi-hop Question Answering [paper] [code]
- [EMNLP 20] Global-to-local neural networks for document-level relation extraction [paper] [code]
- [ACL 20] Reasoning with Latent Structure Refinement for Document-Level Relation Extraction [paper] [code]
- [ACL 19] Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network [paper]
- [ACL 19] Connecting the dots: Document-level neural relation extraction with edge-oriented graphs [paper] [code]
- [Coling 20] Global Context-enhanced Graph Convolutional Networks for Document-level Relation Extraction [paper] [code]
- [ACL 21] From what to why: Improving relation extraction with rationale graph [paper]
- [arXiv 24] KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models [paper]
- [arXiv 25] CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs [paper]
- [arXiv 25] GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation [paper]
- [ICLR 23] Retrieval-based Controllable Molecule Generation [paper] [code]
- [ICML 24] Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation [paper] [code]
- [arXiv 24] MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction [paper] [code]
- [arXiv 24] KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques [paper]
- [arXiv 24] HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses [paper]
- [ACL 24] Mindmap: Knowledge graph prompting sparks graph of thoughts in large language models [paper] [code]
- [EMNLP 24] DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature [paper] [code]
- [ISMB 24] Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models [paper] [code]
- [arXiv 24] Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation [paper] [code]
- [arXiv 24] Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge [paper]
- [arXiv 24] Explainable Biomedical Hypothesis Generation via Retrieval Augmented Generation enabled Large Language Models [paper]
- [arXiv 24] Biomedical knowledge graph-optimized prompt generation for large language models [paper] [code]
- [arXiv 23] Social-LLM: Modeling User Behavior at Scale using Language Models and Social Network Data [paper]
- [WWW 24] Knowledge Graph-based Session Recommendation with Adaptive Propagation [paper]
- [CIKM 24] Topology-aware Retrieval Augmentation for Text Generation [paper]
- [COLING 20] Retrieval-augmented controllable review generation [paper]
- [AAAI 23] Factual and Informative Review Generation for Explainable Recommendation [paper]
- [NLG 18] Cyclegen: Cyclic consistency based product review generator from attributes [paper]
- [EACL 17] Learning to Generate Product Reviews from Attributes [paper]
- [SIGIR 15] Retrieval of Relevant Opinion Sentences for New Products [paper]
- [arXiv 24] Large Language Model with Graph Convolution for Recommendation [paper]
- [WSDM 24] LLMRec: Large Language Models with Graph Augmentation for Recommendation [paper] [code]
- [AAAI 21] Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation [paper] [code]
- [arXiv 24] Federated Recommendation via Hybrid Retrieval Augmented Generation [paper] [code]
- [arXiv 23] Zero-Shot Next-Item Recommendation using Large Pretrained Language Models [paper] [code]
- [TOIS 20] Exploiting Cross-session Information for Session-based Recommendation with Graph Neural Networks [paper]
- [ECIR 24] Large Language Models are Zero-Shot Rankers for Recommender Systems [paper] [code]
- [arXiv 23] Leveraging Large Language Models in Conversational Recommender Systems [paper]
- [arXiv 24] Large Language Models for Social Networks: Applications, Challenges, and Solutions [paper]
- [SIGIR 24] Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking [paper] [code]
- [NeurIPS 24] Benchmarking LLM Retrieval on Semi-structured Knowledge Bases [paper] [code]
- [arXiv 24] CrediRAG: Network-Augmented Credibility-Based Retrieval for Misinformation Detection in Reddit [paper]
- [arXiv 24] Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors [paper]
- [NeurIPS 24] Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face [paper] [code]
- [NeurIPS 24] TaskBench: Benchmarking Large Language Models for Task Automation [paper] [code]
- [arXiv 23] RestGPT: Connecting Large Language Models with Real-World RESTful APIs [paper] [code]
- [NeurIPS 24] Can Graph Learning Improve Planning in LLM-based Agents? [paper] [code]
- [NeurIPS 24] Large language models as commonsense knowledge for large-scale task planning [paper] [code]
- [NeurIPS 23] Large Language Models as Commonsense Knowledge for Large-Scale Task Planning [paper] [code]
- [ICML 24] Graph-enhanced Large Language Models in Asynchronous Plan Reasoning [paper] [code]
- [ACL 21] ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning [paper] [code]
- [ACL 21] Could you give me a hint? generating inference graphs for defeasible reasoning [paper] [code]
- [ICLR 24] ToolChain: Efficient Action Space Navigation in Large Language Models with A Search** [paper]
- [COLM 24] Reasoning with language model is planning with world model [paper] [code]
- [ICCV 23] LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models [paper] [code]
- [MM 24] P-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task [paper]
- [NeurIPS 24] DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph [paper]
- [ACL 23] TabPrompt: Graph-based Pre-training and Prompting for Few-shot Table Understanding [paper]
- [VLDB 22] xFraud: Explainable Fraud Transaction Detection [paper] [code]
- [CIKM 23] GraphFC: Customs fraud detection with label scarcity [paper] [code]
- [AAAI 22] LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks [paper] [code]
- [TKDE 23] Anti-Money Laundering by Group-Aware Deep Graph Learning [paper]
- [AAAI 23] Detecting Multivariate Time Series Anomalies with Zero Known Label [paper] [code]
- [CIKM 19] Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction [paper] [code]
- [NeurIPS 22] Learning Enhanced Representations for Tabular Data via Neighborhood Propagation [paper] [code]
- [KDD 21] Dual Graph enhanced Embedding Neural Network for CTR Prediction [paper] [code]
- [AAAI 23] Data Imputation with Iterative Graph Reconstruction [paper] [code]
- [NeurIPS 20] Handling missing data with graph representation learning [paper] [code]
- [NeurIPS 21] Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach [paper] [code]
- [ICDT 24] Relational Data Imputation with Graph Neural Networks [paper]
- [KDD 21] TUTA: Tree-based Transformers for Generally Structured Table Pre-training [paper] [code]
- [ACL 22] FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining [paper] [code]
- [EMNLP 23] TabPrompt: Graph-based Pre-training and Prompting for Few-shot Table Understanding [paper]
- [AAAI 20] Cfgnn: Cross flow graph neural networks for question answering on complex tables [paper]
- [COLING 20] A Graph Representation of Semi-structured Data for Web Question Answering [paper]
- [SIGIR 21] Retrieving Complex Tables with Multi-Granular Graph Representation Learning [paper] [code]
- [ACL 22] Hitab: A hierarchical table dataset for question answering and natural language generation [paper] [code]
- [arXIv 24] RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models [paper]
- [Iscience 21] Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks [paper] [code]
- [ICML-CB 20] scGNN: scRNA-seq Dropout Imputation via Induced Hierarchical Cell Similarity Graph [paper] [code]
- [NC 21] scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses [paper] [code]
- [BMC 21] An efficient scRNA-seq dropout imputation method using graph attention network [paper] [code]
- [NeurIPS-AI4Sci 22] Bi-channel Masked Graph Autoencoders for Spatially Resolved Single-cell Transcriptomics Data Imputation [paper]
- [Bioinformatics 21] GNN-based embedding for clustering scRNA-seq data [paper] [code]
- [AAAI 22] ZINB-Based Graph Embedding Autoencoder for Single-Cell RNA-Seq Interpretations [paper] [code]
- [Bioinformatics 22] Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network [paper] [code]
- [Bioinformatics 22] scGAC: a graph attentional architecture for clustering single-cell RNA-seq data [paper] [code]
- [KDD 22] Graph Neural Networks for Multimodal Single-Cell Data Integration [paper] [code]
- [JCB 24] SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology [paper] [code]
- [Bioinformatics 21] Deconvoluting Spatial Transcriptomics data through Graph-based convolutional networks [paper] [code]
- [Nature Methods 21] SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network [paper] [code]
- [NC 22] Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder [paper] [code]
- [arXiv 24] G-retriever: Retrieval-augmented generation for textual graph understanding and question answering [paper] [code]
- [MM 24] P-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task [paper]
- [ICLR 24] Talk like a graph: Encoding graphs for large language models [paper]
- [arXiv 23] Graphllm: Boosting graph reasoning ability of large language model [paper] [code]
- [ICML 24] The pitfalls of next-token prediction [paper] [code]
- [arXiv 24] Revisiting the Graph Reasoning Ability of Large Language Models: Case Studies in Translation, Connectivity and Shortest Path [paper] [code]
- [NeurIPS 23] Can language models solve graph problems in natural language? [paper] [code]
- [arXiv 23] Gpt4graph: Can large language models understand graph-structured data? an empirical evaluation and benchmarking [paper]
- [arXiv 24] GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability [paper] [code]
- [arXiv] Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks[paper][code]
- [arXiv] Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation [paper][code]
- [arXiv] HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases [paper]
- [ICLR Openreview 2025] Multi-Field Adaptive Retrieval [paper]
- [EMNLP 2024] Crafting Personalized Agents through Retrieval-Augmented Generation on Editable Memory Graphs [paper]
- [arXiv] GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation [paper]
- [arXiv] GraphRAG under Fire [paper]
This page is contributed and maintained by:
- Yu Wang ([email protected])
- Haoyu Han ([email protected])
- Harry Shomer ([email protected])
- Kai Guo ([email protected])
- Jiayuan Ding ([email protected])
- Yongjia Lei ([email protected])
