Aussie AI

Knowledge Graphs

  • Last Updated 22 October, 2025
  • by David Spuler, Ph.D.

Research on Knowledge Graphs

Research papers include:

  • Shenzhe Zhu, 6 May 2024, Exploring knowledge graph-based neural-symbolic system from application perspective, https://arxiv.org/abs/2405.03524 (Integrate knowledge graph and symbolic reasoning into neural networks.)
  • GG Klager, March 12, 2024, Is GPT fit for KGQA? Masters Thesis, Department of Information Systems & Operations Management, Vienna University of Economics and Business, https://aic.ai.wu.ac.at/~polleres/supervised_theses/Gerhard_Klager_MSc_2024.pdf
  • Louis-François Bouchard, Aug 12, 2024, When to Use GraphRAG, https://louisbouchard.substack.com/p/when-to-use-graphrag
  • Bhaskarjit Sarmah, Benika Hall, Rohan Rao, Sunil Patel, Stefano Pasquali, Dhagash Mehta, 9 Aug 2024, HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction, https://arxiv.org/abs/2408.04948
  • Dr. Ashish Bamania, Aug 2024, ‘MedGraphRAG’ Is A Complete Game Changer For AI In Medicine A deep-dive into how RAG, GraphRAG, and MedGraphRAG work and how they significantly improve the performance of LLM responses in Medicine, https://levelup.gitconnected.com/medgraphrag-is-a-complete-game-changer-for-ai-in-medicine-c6b41b0effd6
  • Junde Wu, Jiayuan Zhu, Yunli Qi, 8 Aug 2024, Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation, https://arxiv.org/abs/2408.04187 Code: https://github.com/MedicineToken/Medical-Graph-RAG/tree/main
  • Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao, 26 May 2024, GRAG: Graph Retrieval-Augmented Generation, https://arxiv.org/abs/2405.16506
  • Philip Rathle, Jul 11, 2024, The GraphRAG Manifesto: Adding Knowledge to GenAI, https://neo4j.com/blog/graphrag-manifesto/
  • Microsoft, Aug 2024 (accessed), GraphRAG: A modular graph-based Retrieval-Augmented Generation (RAG) system, https://github.com/microsoft/graphrag
  • Harry Li, Gabriel Appleby, Ashley Suh, 7 Jun 2024, LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering, https://arxiv.org/abs/2406.06621
  • Xuan Chen, Tong Lu, Zhichun Wang, 6 Dec 2024, LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs, https://arxiv.org/abs/2412.04690
  • Lei Liang, Mengshu Sun, Zhengke Gui, Zhongshu Zhu, Zhouyu Jiang, Ling Zhong, Yuan Qu, Peilong Zhao, Zhongpu Bo, Jin Yang, Huaidong Xiong, Lin Yuan, Jun Xu, Zaoyang Wang, Zhiqiang Zhang, Wen Zhang, Huajun Chen, Wenguang Chen, Jun Zhou, 26 Sep 2024 (v3), KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation, https://arxiv.org/abs/2409.13731
  • Mayi Xu, Yunfeng Ning, Yongqi Li, Jianhao Chen, Jintao Wen, Yao Xiao, Shen Zhou, Birong Pan, Zepeng Bao, Xin Miao, Hankun Kang, Ke Sun, Tieyun Qian, 2 Jan 2025, Reasoning based on symbolic and parametric knowledge bases: a survey, https://arxiv.org/abs/2501.01030 (Extensive survey of reasoning from CoT to knowledge graphs to table-based reasoning.)
  • Alhassan Mumuni, Fuseini Mumuni, 6 Jan 2025, Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches, https://arxiv.org/abs/2501.03151
  • Aidan Hogan, Xin Luna Dong, Denny Vrandečić, Gerhard Weikum, 12 Jan 2025, Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions, https://arxiv.org/abs/2501.06699 (Classic search engines versus LLMs with knowledge graphs with a categorization of search use cases.)
  • Tiesunlong Shen, Jin Wang1, Xuejie Zhang, Erik Cambria, Jan 2025, Reasoning with Trees: Faithful Question Answering over Knowledge Graph, Proceedings of the 31st International Conference on Computational Linguistics, pages 3138–3157 January 19–24, 2025, Association for Computational Linguistics, https://aclanthology.org/2025.coling-main.211.pdf
  • Yuxing Lu, Sin Yee Goi, Xukai Zhao, Jinzhuo Wang, 22 Jan 2025 (v2), Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications, https://arxiv.org/abs/2501.11632
  • Maria Korolov, 29 Jan 2025, Knowledge graphs: the missing link in enterprise AI, CIO, https://www.cio.com/article/3808569/knowledge-graphs-the-missing-link-in-enterprise-ai.html
  • Junde Wu, Jiayuan Zhu, Yuyuan Liu, 7 Feb 2025, Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research, https://arxiv.org/abs/2502.04644 https://github.com/theworldofagents/Agentic-Reasoning
  • Pengcheng Huang, Zhenghao Liu, Yukun Yan, Xiaoyuan Yi, Hao Chen, Zhiyuan Liu, Maosong Sun, Tong Xiao, Ge Yu, Chenyan Xiong, 21 Feb 2025, PIP-KAG: Mitigating Knowledge Conflicts in Knowledge-Augmented Generation via Parametric Pruning, https://arxiv.org/abs/2502.15543
  • Han Zhang, Langshi Zhou, Hanfang Yang, 20 Feb 2025, Learning to Retrieve and Reason on Knowledge Graph through Active Self-Reflection, https://arxiv.org/abs/2502.14932
  • Anastasios Nentidis, Charilaos Akasiadis, Angelos Charalambidis, Alexander Artikis, 26 Feb 2025, Dealing with Inconsistency for Reasoning over Knowledge Graphs: A Survey, https://arxiv.org/abs/2502.19023
  • R Chen, Mar 2025, Retrieval-Augmented Generation with Knowledge Graphs: A Survey Computer Science Undergradaute Conference 2025, https://openreview.net/pdf?id=ZikTuGY28C
  • Khorashadizadeh Hanieh, Amara Fatima Zahra, Ezzabady Morteza, Ieng Frédéric, Tiwari Sanju, et al.. Research Trends for the Interplay between Large Language Models and Knowledge Graphs. 1st International Workshop on Data Management Opportunities in Unifying Large Language Models + Knowledge Graph. Workshop at the 50th International Conference on Very Large Data Bases (VLDB 2024), Aug 2024, Guangzhou, China. hal-04770598 https://hal.science/hal-04770598/document
  • Ziheng Zhang, Zhenxi Lin, Yefeng Zheng, and Xian Wu. 2025. How much Medical Knowledge do LLMs have? An Evaluation of Medical Knowledge Coverage for LLMs. In Proceedings of the ACM on Web Conference 2025 (WWW '25). Association for Computing Machinery, New York, NY, USA, 5330–5341. https://doi.org/10.1145/3696410.3714535 https://dl.acm.org/doi/abs/10.1145/3696410.3714535 https://dl.acm.org/doi/pdf/10.1145/3696410.3714535
  • Chuzhan Hao, Wenfeng Feng, Yuewei Zhang, Hao Wang, 23 Jul 2025, DynaSearcher: Dynamic Knowledge Graph Augmented Search Agent via Multi-Reward Reinforcement Learning, https://arxiv.org/abs/2507.17365
  • Qikai Wei and Huansheng Ning and Chunlong Han and Jianguo Ding, 7 Jul 2025, A Query-Aware Multi-Path Knowledge Graph Fusion Approach for Enhancing Retrieval-Augmented Generation in Large Language Models, https://arxiv.org/abs/2507.16826
  • Mingda Zhang, Na Zhao, Jianglong Qin, Guoyu Ye, Ruixiang Tang, 22 Jul 2025, A Multi-granularity Concept Sparse Activation and Hierarchical Knowledge Graph Fusion Framework for Rare Disease Diagnosis, https://arxiv.org/abs/2507.08529
  • Junming Liu, Siyuan Meng, Yanting Gao, Song Mao, Pinlong Cai, Guohang Yan, Yirong Chen, Zilin Bian, Ding Wang, Botian Shi, 24 Jul 2025, Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning, https://arxiv.org/abs/2503.12972
  • Bhishma Dedhia, Yuval Kansal, Niraj K. Jha, 18 Jul 2025, Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need, https://arxiv.org/abs/2507.13966
  • Arief Purnama Muharram and Ayu Purwarianti, 21 Jul 2025, Enhancing Natural Language Inference Performance with Knowledge Graph for COVID-19 Automated Fact-Checking in Indonesian Language, https://arxiv.org/abs/2409.00061
  • Xueli Pan, Victor de Boer, Jacco van Ossenbruggen, 14 Aug 2025, FIRESPARQL: A LLM-based Framework for SPARQL Query Generation over Scholarly Knowledge Graphs, https://arxiv.org/abs/2508.10467
  • Rishi Parekh, Saisubramaniam Gopalakrishnan, Zishan Ahmad, Anirudh Deodhar, 23 Jul 2025, Leveraging Knowledge Graphs and LLM Reasoning to Identify Operational Bottlenecks for Warehouse Planning Assistance, https://arxiv.org/abs/2507.17273
  • Aleksandr Perevalov, Andreas Both, 22 Jul 2025, Text-to-SPARQL Goes Beyond English: Multilingual Question Answering Over Knowledge Graphs through Human-Inspired Reasoning, https://arxiv.org/abs/2507.16971
  • Haoran Jiang, Shaohan Shi, Yunjie Yao, Chang Jiang, Quan Li, 23 Jul 2025, HypoChainer: A Collaborative System Combining LLMs and Knowledge Graphs for Hypothesis-Driven Scientific Discovery, https://arxiv.org/abs/2507.17209
  • Jianhao Chen, Junyang Ren, Wentao Ding, Haoyuan Ouyang, Wei Hu, Yuzhong Qu, 23 Jul 2025, Conflict Detection for Temporal Knowledge Graphs:A Fast Constraint Mining Algorithm and New Benchmarks, https://arxiv.org/abs/2312.11053
  • Adrian Kaiser and Claudiu Leoveanu-Condrei and Ryan Gold and Marius-Constantin Dinu and Markus Hofmarcher, 23 Jul 2025, HyDRA: A Hybrid-Driven Reasoning Architecture for Verifiable Knowledge Graphs, https://arxiv.org/abs/2507.15917
  • Jean Lelong, Adnane Errazine and Annabelle Blangero, 22 Jul 2025, Agentic RAG with Knowledge Graphs for Complex Multi-Hop Reasoning in Real-World Applications, https://arxiv.org/abs/2507.16507
  • Mingda Zhang, Na Zhao, Jianglong Qing, Qing xu, Kaiwen Pan, Ting luo, 22 Jul 2025, An Integrated Framework of Prompt Engineering and Multidimensional Knowledge Graphs for Legal Dispute Analysis, https://arxiv.org/abs/2507.07893
  • Yuxin Zhang (1), Xi Wang (1), Mo Hu (1), Zhenyu Zhang (1) ((1) Department of Construction Science, College of Architecture, Texas A&M University, College Station, USA), 18 Jul 2025, BifrostRAG: Bridging Dual Knowledge Graphs for Multi-Hop Question Answering in Construction Safety, https://arxiv.org/abs/2507.13625
  • Nur A Zarin Nishat, Andrea Coletta, Luigi Bellomarini, Kossi Amouzouvi, Jens Lehmann, Sahar Vahdati, 17 Jul 2025, Aligning Knowledge Graphs and Language Models for Factual Accuracy, https://arxiv.org/abs/2507.13411
  • Hosein Azarbonyad, Zi Long Zhu, Georgios Cheirmpos, Zubair Afzal, Vikrant Yadav, Georgios Tsatsaronis, 18 Jul 2025, Question-Answer Extraction from Scientific Articles Using Knowledge Graphs and Large Language Models, https://arxiv.org/abs/2507.13827
  • Akash Bajwa and Chia Jeng Yang, May 27, 2024, The RAG Stack: Featuring Knowledge Graphs: Reducing Hallucinations To Make LLMs Production-Grade With Complex RAG, https://akashbajwa.substack.com/p/the-rag-stack-featuring-knowledge
  • Igor Novikov, Jul 23, 2024, RAG Architecture: Advanced RAG, https://pub.towardsai.net/rag-architecture-advanced-rag-3fea83e0d189
  • Junda Wu, Xintong Li, Ruoyu Wang, Yu Xia, Yuxin Xiong, Jianing Wang, Tong Yu, Xiang Chen, Branislav Kveton, Lina Yao, Jingbo Shang, Julian McAuley, 31 Oct 2024, OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models, https://arxiv.org/abs/2410.23703
  • Jaikrishna Manojkumar Patil, Nathaniel Lee, Al Mehdi Saadat Chowdhury, YooJung Choi, Paulo Shakarian, 8 Aug 2025, Probabilistic Circuits for Knowledge Graph Completion with Reduced Rule Sets, https://arxiv.org/abs/2508.06706
  • Yongkang Xiao, Rui Zhang, 8 Aug 2025, HERGC: Heterogeneous Experts Representation and Generative Completion for Multimodal Knowledge Graphs, https://arxiv.org/abs/2506.00826
  • Yuzhang Xie, Xu Han, Ran Xu, Xiao Hu, Jiaying Lu, Carl Yang, 26 Jul 2025, HypKG: Hypergraph-based Knowledge Graph Contextualization for Precision Healthcare, https://arxiv.org/abs/2507.19726
  • Alec Scully, Cameron Stockton, and Forrest Hare, 26 Jul 2025, Integrating Activity Predictions in Knowledge Graphs, https://arxiv.org/abs/2507.19733
  • Keyan Ding, Jing Yu, Junjie Huang, Yuchen Yang, Qiang Zhang, Huajun Chen, 27 Jul 2025, SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration, https://arxiv.org/abs/2507.20280
  • Jiajun Liu, Wenjun Ke, Peng Wang, Yao He, Ziyu Shang, Guozheng Li, Zijie Xu, and Ke Ji, 28 Jul 2025, Unlearning of Knowledge Graph Embedding via Preference Optimization, https://arxiv.org/abs/2507.20566
  • Lijian Li, 28 Jul 2025, Complementarity-driven Representation Learning for Multi-modal Knowledge Graph Completion, https://arxiv.org/abs/2507.20620
  • Xueyao Wan, Hang Yu, 28 Jul 2025, MMGraphRAG: Bridging Vision and Language with Interpretable Multimodal Knowledge Graphs, https://arxiv.org/abs/2507.20804
  • Enjun Du, Siyi Liu, Yongqi Zhang, 28 Jul 2025, Mixture of Length and Pruning Experts for Knowledge Graphs Reasoning, https://arxiv.org/abs/2507.20498
  • Wenbin Guo, Xin Wang, Jiaoyan Chen, Zhao Li and Zirui Chen, 28 Jul 2025, Ontology-Enhanced Knowledge Graph Completion using Large Language Models, https://arxiv.org/abs/2507.20643
  • Muhammad Tayyab Khan, Lequn Chen, Wenhe Feng and Seung Ki Moon, 28 Jul 2025, Large Language Model Powered Decision Support for a Metal Additive Manufacturing Knowledge Graph, https://arxiv.org/abs/2505.20308
  • Hao Ye, Mengshi Qi, Zhaohong Liu, Liang Liu and Huadong Ma, 29 Jul 2025, SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generation, https://arxiv.org/abs/2507.21585
  • Alessandro Lonardi and Samy Badreddine and Tarek R. Besold and Pablo Sanchez Martin, 29 Jul 2025, Unifying Post-hoc Explanations of Knowledge Graph Completions, https://arxiv.org/abs/2507.22951
  • Nasim Shirvani-Mahdavi, Devin Wingfield, Amin Ghasemi, Chengkai Li, 31 Jul 2025, Rule2Text: Natural Language Explanation of Logical Rules in Knowledge Graphs, https://arxiv.org/abs/2507.23740
  • Jiaxin Bai, Wei Fan, Qi Hu, Qing Zong, Chunyang Li, Hong Ting Tsang, Hongyu Luo, Yauwai Yim, Haoyu Huang, Xiao Zhou, Feng Qin, Tianshi Zheng, Xi Peng, Xin Yao, Huiwen Yang, Leijie Wu, Yi Ji, Gong Zhang, Renhai Chen, Yangqiu Song, 31 Jul 2025, AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora, https://arxiv.org/abs/2505.23628
  • Tung-Wei Lin, Gabe Fierro, Han Li, Tianzhen Hong, Pierluigi Nuzzo, Alberto Sangiovanni-Vinentelli, 30 Jul 2025, Systematic Evaluation of Knowledge Graph Repair with Large Language Models, https://arxiv.org/abs/2507.22419
  • Thanh Hoang-Minh, 30 Jul 2025, Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs, https://arxiv.org/abs/2507.03947
  • Antonis Klironomos, Baifan Zhou, Zhipeng Tan, Zhuoxun Zheng, Mohamed H. Gad-Elrab, Heiko Paulheim, Evgeny Kharlamov, 1 Aug 2025, ExeKGLib: A Platform for Machine Learning Analytics based on Knowledge Graphs, https://arxiv.org/abs/2508.00394
  • Yuanyuan Liang, Xiaoman Wang, Tingyu Xie, and Lei Pan, 3 Aug 2025, ProKG-Dial: Progressive Multi-Turn Dialogue Construction with Domain Knowledge Graphs, https://arxiv.org/abs/2508.01869
  • Hanchen Yang, Jiaqi Wang, Jiannong Cao, Wengen Li, Jialun Zheng, Yangning Li, Chunyu Miao, Jihong Guan, Shuigeng Zhou, and Philip S. Yu, 31 Jul 2025, OKG-LLM: Aligning Ocean Knowledge Graph with Observation Data via LLMs for Global Sea Surface Temperature Prediction, https://arxiv.org/abs/2508.00933
  • Xiang Li, Penglei Sun, Wanyun Zhou, Zikai Wei, Yongqi Zhang, Xiaowen Chu, 1 Aug 2025, FinKario: Event-Enhanced Automated Construction of Financial Knowledge Graph, https://arxiv.org/abs/2508.00961
  • Wei Zhou, Peng Sun, Xuanhe Zhou, Qianglei Zang, Ji Xu, Tieying Zhang, Guoliang Li, Fan Wu, 2 Aug 2025, DBAIOps: A Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs, https://arxiv.org/abs/2508.01136
  • Yang Zhao, Chengxiao Dai, Wei Zhuo, Tan Chuan Fu, Yue Xiu, Dusit Niyato, Jonathan Z. Low, Eugene Ho Hong Zhuang, Daren Zong Loong Tan, 3 Aug 2025, AGENTICT$^2$S:Robust Text-to-SPARQL via Agentic Collaborative Reasoning over Heterogeneous Knowledge Graphs for the Circular Economy, https://arxiv.org/abs/2508.01815
  • Linyu Li, Zhi Jin, Yuanpeng He, Dongming Jin, Yichi Zhang, Haoran Duan, Nyima Tash, 4 Aug 2025, Learning to Evolve: Bayesian-Guided Continual Knowledge Graph Embedding, https://arxiv.org/abs/2508.02426
  • Xinjie Zhao, Moritz Blum, Fan Gao, Yingjian Chen, Boming Yang, Luis Marquez-Carpintero, M\'onica Pina-Navarro, Yanran Fu, So Morikawa, Yusuke Iwasawa, Yutaka Matsuo, Chanjun Park, Irene Li, 5 Aug 2025, AGENTiGraph: A Multi-Agent Knowledge Graph Framework for Interactive, Domain-Specific LLM Chatbots, https://arxiv.org/abs/2508.02999
  • Taine J. Elliott, Stephen P. Levitt, Ken Nixon and Martin Bekker, 5 Aug 2025, Data Overdose? Time for a Quadruple Shot: Knowledge Graph Construction using Enhanced Triple Extraction, https://arxiv.org/abs/2508.03438
  • Yubo Wang, Shimin Di, Zhili Wang, Haoyang Li, Fei Teng, Hao Xin and Lei Chen, 5 Aug 2025, Understanding the Embedding Models on Hyper-relational Knowledge Graph, https://arxiv.org/abs/2508.03280
  • Ge Shi, Kaiyu Huang, Guochen Feng, 5 Aug 2025, Long Story Generation via Knowledge Graph and Literary Theory, https://arxiv.org/abs/2508.03137
  • Futian Wang, Yuhan Qiao, Xiao Wang, Fuling Wang, Yuxiang Zhang, Dengdi Sun, 5 Aug 2025, R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generation, https://arxiv.org/abs/2508.03426
  • Nandana Mihindukulasooriya, Niharika S. D'Souza, Faisal Chowdhury, Horst Samulowitz, 4 Aug 2025, Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Study, https://arxiv.org/abs/2506.19773
  • Hudson de Martim, 5 Aug 2025, A Foundational Schema.org Mapping for a Legal Knowledge Graph: Representing Brazilian Legal Norms as FRBR Works, https://arxiv.org/abs/2508.00827
  • Ruochen Zhao, Simone Conia, Eric Peng, Min Li, Saloni Potdar, 6 Aug 2025, AgREE: Agentic Reasoning for Knowledge Graph Completion on Emerging Entities, https://arxiv.org/abs/2508.04118
  • Qian Yong, Yanhui Li, Jialiang Shi, Yaguang Dou, Tian Qi, 6 Aug 2025, Enhancing Serendipity Recommendation System by Constructing Dynamic User Knowledge Graphs with Large Language Models, https://arxiv.org/abs/2508.04032
  • Krzysztof Olejniczak, Xingyue Huang, Mikhail Galkin, \.Ismail \.Ilkan Ceylan, 5 Aug 2025, One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs, https://arxiv.org/abs/2409.13959
  • Ge Chang, Jinbo Su, Jiacheng Liu, Pengfei Yang, Yuhao Shang, Huiwen Zheng, Hongli Ma, Yan Liang, Yuanchun Li, Yunxin Liu, 7 Aug 2025, GRAIL:Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning, https://arxiv.org/abs/2508.05498
  • Claudia d'Amato, Ivan Diliso, Nicola Fanizzi, Zafar Saeed, 7 Aug 2025, Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models, https://arxiv.org/abs/2508.05587
  • Xu Yuan, Liangbo Ning, Wenqi Fan, Qing Li, 7 Aug 2025, mKG-RAG: Multimodal Knowledge Graph-Enhanced RAG for Visual Question Answering, https://arxiv.org/abs/2508.05318
  • Claudia dAmato, Giuseppe Rubini, Francesco Didio, Donato Francioso, Fatima Zahra Amara, Nicola Fanizzi, 8 Aug 2025, Automated Creation of the Legal Knowledge Graph Addressing Legislation on Violence Against Women: Resource, Methodology and Lessons Learned, https://arxiv.org/abs/2508.06368
  • Siamak Farshidi and Amir Saberhabibi and Behbod Eskafi and Niloofar Nikfarjam and Sadegh Eskandari and Slinger Jansen and Michel Chaudron and Bedir Tekinerdogan, 6 Aug 2025, Empirical Evaluation of AI-Assisted Software Package Selection: A Knowledge Graph Approach, https://arxiv.org/abs/2508.05693
  • Congmin Min, Rhea Mathew, Joyce Pan, Sahil Bansal, Abbas Keshavarzi, Amar Viswanathan Kannan, 7 Aug 2025, Efficient Knowledge Graph Construction and Retrieval from Unstructured Text for Large-Scale RAG Systems, https://arxiv.org/abs/2507.03226
  • Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang, Hongkuan Zhou, Yuan He, Jiaoyan Chen, Evgeny Kharlamov, Steffen Staab, 11 Aug 2025, What Breaks Knowledge Graph based RAG? Empirical Insights into Reasoning under Incomplete Knowledge, https://arxiv.org/abs/2508.08344
  • Roberto Barile, Claudia d'Amato, Nicola Fanizzi, 12 Aug 2025, GRainsaCK: a Comprehensive Software Library for Benchmarking Explanations of Link Prediction Tasks on Knowledge Graphs, https://arxiv.org/abs/2508.08815
  • Bhavik Agarwal, Hemant Sunil Jomraj, Simone Kaplunov, Jack Krolick, Viktoria Rojkova, 13 Aug 2025, RAGulating Compliance: A Multi-Agent Knowledge Graph for Regulatory QA, https://arxiv.org/abs/2508.09893
  • Yuheng Wang, Tianze Yu, Jiayue Cai, Sunil Kalia, Harvey Lui, Z. Jane Wang, Tim K. Lee, 13 Aug 2025, Integrating Clinical Knowledge Graphs and Gradient-Based Neural Systems for Enhanced Melanoma Diagnosis via the 7-Point Checklist, https://arxiv.org/abs/2407.16822
  • Yifei Li, Lingling Zhang, Hang Yan, Tianzhe Zhao, Zihan Ma, Muye Huang, Jun Liu, 15 Aug 2025, SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding, https://arxiv.org/abs/2508.11347
  • Nasim Shirvani-Mahdavi, Chengkai Li, 14 Aug 2025, Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules, https://arxiv.org/abs/2508.10971
  • Duzhen Zhang, Zixiao Wang, Zhong-Zhi Li, Yahan Yu, Shuncheng Jia, Jiahua Dong, Haotian Xu, Xing Wu, Yingying Zhang, Tielin Zhang, Jie Yang, Xiuying Chen, Le Song, 17 Aug 2025, MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph, https://arxiv.org/abs/2508.12393
  • Ziteng Hu, Yingjie Xia, Xiyuan Chen, Li Kuang, 18 Aug 2025, SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip, https://arxiv.org/abs/2508.12910
  • Hung Nghiep Tran, Atsuhiro Takasu, 15 Aug 2025, Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space, https://arxiv.org/abs/1909.08191
  • Daniel Daza, Alberto Bernardi, Luca Costabello, Christophe Gueret, Masoud Mansoury, Michael Cochez, Martijn Schut, 19 Aug 2025, Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints, https://arxiv.org/abs/2508.13663
  • Mariam Arustashvili, J\"org Deigm\"oller, Heiko Paulheim, 19 Aug 2025, Knowledge Graph Completion for Action Prediction on Situational Graphs -- A Case Study on Household Tasks, https://arxiv.org/abs/2508.13675
  • Yang Xiao, Ruimeng Ye, Bohan Liu, Xiaolong Ma, Bo Hui, 19 Aug 2025, Efficient Knowledge Graph Unlearning with Zeroth-order Information, https://arxiv.org/abs/2508.14013
  • Peilin Ji, Xiao Xue, Simeng Wang, Wenhao Yan, 20 Aug 2025, Entropy-Constrained Strategy Optimization in Urban Floods: A Multi-Agent Framework with LLM and Knowledge Graph Integration, https://arxiv.org/abs/2508.14654
  • Dennis Schiese, Aleksandr Perevalov, Andreas Both, 20 Aug 2025, Towards LLM-generated explanations for Component-based Knowledge Graph Question Answering Systems, https://arxiv.org/abs/2508.14553
  • Haji Gul, Abul Ghani Naim, Ajaz Ahmad Bhat, 21 Aug 2025, Evaluating Knowledge Graph Complexity via Semantic, Spectral, and Structural Metrics for Link Prediction, https://arxiv.org/abs/2508.15291
  • Runxuan Liu, Bei Luo, Jiaqi Li, Baoxin Wang, Ming Liu, Dayong Wu, Shijin Wang, Bing Qin, 21 Aug 2025, Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering, https://arxiv.org/abs/2502.11491
  • Nan Wang, Yongqi Fan, yansha zhu, ZongYu Wang, Xuezhi Cao, Xinyan He, Haiyun Jiang, Tong Ruan, Jingping Liu, 12 Aug 2025, KG-o1: Enhancing Multi-hop Question Answering in Large Language Models via Knowledge Graph Integration, https://arxiv.org/abs/2508.15790
  • Ryoma Kondo, Riona Matsuoka, Takahiro Yoshida, Kazuyuki Yamasawa, Ryohei Hisano, 24 Aug 2025, Capturing Legal Reasoning Paths from Facts to Law in Court Judgments using Knowledge Graphs, https://arxiv.org/abs/2508.17340
  • Yitong Lin, Jiaying He, Jiahe Chen, Xinnan Zhu, Jianwei Zheng, Tao Bo, 22 Jul 2025, BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning, https://arxiv.org/abs/2507.14468
  • Jialiang Wang, Hanmo Liu, Shimin Di, Zhili Wang, Jiachuan Wang, Lei Chen, Xiaofang Zhou, 21 Jul 2025, Proficient Graph Neural Network Design by Accumulating Knowledge on Large Language Models, https://arxiv.org/abs/2408.06717
  • Mubaris Nadeem, Johannes Zenkert, Lisa Bender, Christian Weber, Madjid Fathi, 11 Aug 2025, KIRETT: Knowledge-Graph-Based Smart Treatment Assistant for Intelligent Rescue Operations, https://arxiv.org/abs/2508.07834
  • Yaoze Zhang, Rong Wu, Pinlong Cai, Xiaoman Wang, Guohang Yan, Song Mao, Ding Wang, Botian Shi, 14 Aug 2025, LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval, https://arxiv.org/abs/2508.10391
  • Robert Frenken, Sidra Ghayour Bhatti, Hanqin Zhang, Qadeer Ahmed, 25 Jul 2025, KD-GAT: Combining Knowledge Distillation and Graph Attention Transformer for a Controller Area Network Intrusion Detection System, https://arxiv.org/abs/2507.19686
  • Zhaoyan Wang, Hyunjun Ahn, In-Young Ko, 28 Jul 2025, Beyond Interactions: Node-Level Graph Generation for Knowledge-Free Augmentation in Recommender Systems, https://arxiv.org/abs/2507.20578
  • Zhen Wu, Ritam Dutt, Luke M. Breitfeller, Armineh Nourbakhsh, Siddharth Parekh, Carolyn Ros\'e, 2 Aug 2025, $R^2$-CoD: Understanding Text-Graph Complementarity in Relational Reasoning via Knowledge Co-Distillation, https://arxiv.org/abs/2508.01475
  • Jiayi Wen, Tianxin Chen, Zhirun Zheng, Cheng Huang, 6 Aug 2025, A Few Words Can Distort Graphs: Knowledge Poisoning Attacks on Graph-based Retrieval-Augmented Generation of Large Language Models, https://arxiv.org/abs/2508.04276
  • Zhu Xu, Ting Lei, Zhimin Li, Guan Wang, Qingchao Chen, Yuxin Peng, Yang liu, 7 Aug 2025, TRKT: Weakly Supervised Dynamic Scene Graph Generation with Temporal-enhanced Relation-aware Knowledge Transferring, https://arxiv.org/abs/2508.04943
  • Daniel Airinei, Elena Burceanu, Marius Leordeanu, 15 Aug 2025, Inside Knowledge: Graph-based Path Generation with Explainable Data Augmentation and Curriculum Learning for Visual Indoor Navigation, https://arxiv.org/abs/2508.11446
  • Bowen Wang, Zhouqiang Jiang, Yasuaki Susumu, Shotaro Miwa, Tianwei Chen, Yuta Nakashima, 25 Aug 2025, Taming the Untamed: Graph-Based Knowledge Retrieval and Reasoning for MLLMs to Conquer the Unknown, https://arxiv.org/abs/2506.17589
  • Zahra Zehtabi Sabeti Moghaddam, Zeinab Dehghani, Maneeha Rani, Koorosh Aslansefat, Bhupesh Kumar Mishra, Rameez Raja Kureshi, Dhavalkumar Thakker, 3 Sep 2025, Explainable Knowledge Graph Retrieval-Augmented Generation (KG-RAG) with KG-SMILE, https://arxiv.org/abs/2509.03626
  • Kishor Datta Gupta, Mohd Ariful Haque, Hasmot Ali, Marufa Kamal, Syed Bahauddin Alam, and Mohammad Ashiqur Rahman, 4 Sep 2025, Continuous Monitoring of Large-Scale Generative AI via Deterministic Knowledge Graph Structures, https://arxiv.org/abs/2509.03857
  • Shanglin Wu, Lihui Liu, Jinho D. Choi, Kai Shu, 31 Aug 2025, Improving Factuality in LLMs via Inference-Time Knowledge Graph Construction, https://arxiv.org/abs/2509.03540
  • Zhaoyan Gong, Juan Li, Zhiqiang Liu, Lei Liang, Huajun Chen, Wen Zhang, 4 Sep 2025, RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models, https://arxiv.org/abs/2509.03995
  • Farnoosh Hashemi, Laks V.S. Lakshmanan, 4 Sep 2025, KRAFT: A Knowledge Graph-Based Framework for Automated Map Conflation, https://arxiv.org/abs/2509.04684
  • Zhangding Liu, Neda Mohammadi, and John E. Taylor, 5 Sep 2025, FloodVision: Urban Flood Depth Estimation Using Foundation Vision-Language Models and Domain Knowledge Graph, https://arxiv.org/abs/2509.04772
  • Xiaoxiong Zhang, Zhiwei Zeng, Xin Zhou, Zhiqi Shen, 5 Sep 2025, Low-Dimensional Federated Knowledge Graph Embedding via Knowledge Distillation, https://arxiv.org/abs/2408.05748
  • Nitin Nagesh Kulkarni, Bryson Wilcox, Max Sawa, Jason Thom, 25 Aug 2025, PKG-DPO: Optimizing Domain-Specific AI systems with Physics Knowledge Graphs and Direct Preference Optimization, https://arxiv.org/abs/2508.18391
  • Honghao Fu, Junlong Ren, Qi Chai, Deheng Ye, Yujun Cai, Hao Wang, 26 Aug 2025, VistaWise: Building Cost-Effective Agent with Cross-Modal Knowledge Graph for Minecraft, https://arxiv.org/abs/2508.18722
  • Rikuto Kotoge, Ziwei Yang, Zheng Chen, Yushun Dong, Yasuko Matsubara, Jimeng Sun, Yasushi Sakurai, 28 Aug 2025, ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation, https://arxiv.org/abs/2502.18026
  • Tingxuan Xu, Jiarui Feng, Justin Melendez, Kaleigh Roberts, Donghong Cai, Mingfang Zhu, Donald Elbert, Yixin Chen, Randall J. Bateman, 28 Aug 2025, Addressing accuracy and hallucination of LLMs in Alzheimer's disease research through knowledge graphs, https://arxiv.org/abs/2508.21238
  • Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang, Yuan He, Jiaoyan Chen, Steffen Staab, Evgeny Kharlamov, 29 Aug 2025, Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness, https://arxiv.org/abs/2504.05163
  • Brian Wang, Mani Srivastava, 30 Aug 2025, SIGMUS: Semantic Integration for Knowledge Graphs in Multimodal Urban Spaces, https://arxiv.org/abs/2509.00287
  • Jiasheng Xu, Mingda Li, Yongqiang Tang, Peijie Wang, Wensheng Zhang, 1 Sep 2025, Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework, https://arxiv.org/abs/2509.01238
  • Sergio Consoli, Pietro Coletti, Peter V. Markov, Lia Orfei, Indaco Biazzo, Lea Schuh, Nicolas Stefanovitch, Lorenzo Bertolini, Mario Ceresa, Nikolaos I. Stilianakis, 2 Sep 2025, An Epidemiological Knowledge Graph extracted from the World Health Organization's Disease Outbreak News, https://arxiv.org/abs/2509.02258
  • Susana Nunes, Samy Badreddine, Catia Pesquita, 2 Sep 2025, Rewarding Explainability in Drug Repurposing with Knowledge Graphs, https://arxiv.org/abs/2509.02276
  • Haimei Pan, Jiyun Zhang, Qinxi Wei, Xiongnan Jin, Chen Xinkai, Jie Cheng, 25 Aug 2025, Robotic Fire Risk Detection based on Dynamic Knowledge Graph Reasoning: An LLM-Driven Approach with Graph Chain-of-Thought, https://arxiv.org/abs/2509.00054
  • Yu Liu, Yanan Cao, Xixun Lin, Yanmin Shang, Shi Wang, Shirui Pan, 1 Sep 2025, Enhancing Large Language Model for Knowledge Graph Completion via Structure-Aware Alignment-Tuning, https://arxiv.org/abs/2509.01166
  • Madan Krishnamurthy, Surya Saha, Pierrette Lo, Patricia L. Whetzel, Tursynay Issabekova, Jamed Ferreris Vargas, Jack DiGiovanna, Melissa A Haendel, 1 Sep 2025, Enabling Down Syndrome Research through a Knowledge Graph-Driven Analytical Framework, https://arxiv.org/abs/2509.01565
  • Zihao Li, Dongqi Fu, Mengting Ai, Jingrui He, 1 Sep 2025, APEX$^2$: Adaptive and Extreme Summarization for Personalized Knowledge Graphs, https://arxiv.org/abs/2412.17336
  • Siyuan Li, Ruitong Liu, Yan Wen, Te Sun, Andi Zhang, Yanbiao Ma, Xiaoshuai Hao, 30 Aug 2025, Flow-Modulated Scoring for Semantic-Aware Knowledge Graph Completion, https://arxiv.org/abs/2506.23137
  • Qurat Ul Ain and Mohamed Amine Chatti and Jean Qussa and Amr Shakhshir and Rawaa Alatrash and Shoeb Joarder, 5 Sep 2025, An Optimized Pipeline for Automatic Educational Knowledge Graph Construction, https://arxiv.org/abs/2509.05392
  • Rawaa Alatrash and Mohamed Amine Chatti and Nasha Wibowo and Qurat Ul Ain, 5 Sep 2025, Inferring Prerequisite Knowledge Concepts in Educational Knowledge Graphs: A Multi-criteria Approach, https://arxiv.org/abs/2509.05393
  • Mengxue Yang, Chun Yang, Jiaqi Zhu, Jiafan Li, Jingqi Zhang, Yuyang Li, Ying Li, 8 Sep 2025, SLiNT: Structure-aware Language Model with Injection and Contrastive Training for Knowledge Graph Completion, https://arxiv.org/abs/2509.06531
  • Manit Baser, Dinil Mon Divakaran, Mohan Gurusamy, 6 Sep 2025, ThinkEval: Practical Evaluation of Knowledge Leakage in LLM Editing using Thought-based Knowledge Graphs, https://arxiv.org/abs/2506.01386
  • Hamid Ahmad, Heiko Paulheim, Rita T. Sousa, 9 Sep 2025, Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddings, https://arxiv.org/abs/2509.07905
  • Andrey Sakhovskiy, Elena Tutubalina, 9 Sep 2025, BALI: Enhancing Biomedical Language Representations through Knowledge Graph and Language Model Alignment, https://arxiv.org/abs/2509.07588
  • Fernando Spadea and Oshani Seneviratne, 8 Sep 2025, Avoiding Over-Personalization with Rule-Guided Knowledge Graph Adaptation for LLM Recommendations, https://arxiv.org/abs/2509.07133
  • Hudson de Martim, 9 Sep 2025, Modeling the Diachronic Evolution of Legal Norms: An LRMoo-Based, Component-Level, Event-Centric Approach to Legal Knowledge Graphs, https://arxiv.org/abs/2506.07853
  • Mingyang Li, Viktor Schlegel, Tingting Mu, Warren Del-Pinto, Goran Nenadic, 4 Sep 2025, Structured Information Matters: Explainable ICD Coding with Patient-Level Knowledge Graphs, https://arxiv.org/abs/2509.09699
  • Vaibhav Chaudhary, Neha Soni, Narotam Singh, Amita Kapoor, 11 Sep 2025, Fusing Knowledge and Language: A Comparative Study of Knowledge Graph-Based Question Answering with LLMs, https://arxiv.org/abs/2509.09272
  • Julia Gastinger, Christian Meilicke, Heiner Stuckenschmidt, 11 Sep 2025, CountTRuCoLa: Rule Confidence Learning for Temporal Knowledge Graph Forecasting, https://arxiv.org/abs/2509.09474
  • Vadim Zadykian, Bruno Andrade and Haithem Afli, 11 Sep 2025, Towards Explainable Job Title Matching: Leveraging Semantic Textual Relatedness and Knowledge Graphs, https://arxiv.org/abs/2509.09522
  • Junhong Lin, Song Wang, Xiaojie Guo, Julian Shun, Yada Zhu, 18 Sep 2025, Temporal Reasoning with Large Language Models Augmented by Evolving Knowledge Graphs, https://arxiv.org/abs/2509.15464
  • Arvindh Arun, Sumit Kumar, Mojtaba Nayyeri, Bo Xiong, Ponnurangam Kumaraguru, Antonio Vergari, Steffen Staab, 19 Sep 2025, SEMMA: A Semantic Aware Knowledge Graph Foundation Model, https://arxiv.org/abs/2505.20422
  • Mengzheng Yang, Yanfei Ren, David Osei Opoku, Ruochang Li, Peng Ren, Chunxiao Xing, 22 Aug 2025, DSRAG: A Domain-Specific Retrieval Framework Based on Document-derived Multimodal Knowledge Graph, https://arxiv.org/abs/2509.10467
  • Haodi Ma, Dzmitry Kasinets, Daisy Zhe Wang, 15 Sep 2025, Transformer-Based Multimodal Knowledge Graph Completion with Link-Aware Contexts, https://arxiv.org/abs/2501.15688
  • Alberto Cattaneo, Stephen Bonner, Thomas Martynec, Edward Morrissey, Carlo Luschi, Ian P Barrett, Daniel Justus, 18 Sep 2025, The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models, https://arxiv.org/abs/2409.04103
  • Chenjun Li, Laurin Lux, Alexander H. Berger, Martin J. Menten, Mert R. Sabuncu, Johannes C. Paetzold, 17 Sep 2025, Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis, https://arxiv.org/abs/2503.09808
  • Michael Kishelev, Pranab Bhadani, Wanying Ding, Vinay Chaudhri, 9 Sep 2025, JEL: A Novel Model Linking Knowledge Graph entities to News Mentions, https://arxiv.org/abs/2509.08086
  • Przemys{\l}aw Stok{\l}osa, Janusz A. Starzyk, Pawe{\l} Raif, Adrian Horzyk, Marcin Kowalik, 9 Sep 2025, Associative Knowledge Graphs for Efficient Sequence Storage and Retrieval, https://arxiv.org/abs/2411.14480
  • Siyuan Li, Yan Wen, Ruitong Liu, Te Sun, Ruihao Zhou, Jingyi Kang, Yunjia Wu, 10 Sep 2025, Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing, https://arxiv.org/abs/2506.23141
  • Minh Pham Dinh, Munira Syed, Michael G Yankoski, Trenton W. Ford, 17 Sep 2025, DAVIS: Planning Agent with Knowledge Graph-Powered Inner Monologue, https://arxiv.org/abs/2410.09252

AI Books from Aussie AI



The Sweetest Lesson: Your Brain Versus AI The Sweetest Lesson: Your Brain Versus AI: new book on AI intelligence theory:
  • Your brain is 50 times bigger than the best AI engines.
  • Truly intelligent AI will require more compute!
  • Another case of the bitter lesson?
  • Maybe it's the opposite of that: the sweetest lesson.

Get your copy from Amazon: The Sweetest Lesson



RAG Optimization RAG Optimization: Accurate and Efficient LLM Applications: new book on RAG architectures:
  • Smarter RAG
  • Faster RAG
  • Cheaper RAG
  • Agentic RAG
  • RAG reasoning

Get your copy from Amazon: RAG Optimization



Generative AI in C++ Generative AI Applications book:
  • Deciding on your AI project
  • Planning for success and safety
  • Designs and LLM architectures
  • Expediting development
  • Implementation and deployment

Get your copy from Amazon: Generative AI Applications



Generative AI in C++ Generative AI programming book:
  • Generative AI coding in C++
  • Transformer engine speedups
  • LLM models
  • Phone and desktop AI
  • Code examples
  • Research citations

Get your copy from Amazon: Generative AI in C++



CUDA C++ Optimization CUDA C++ Optimization book:
  • Faster CUDA C++ kernels
  • Optimization tools & techniques
  • Compute optimization
  • Memory optimization

Get your copy from Amazon: CUDA C++ Optimization



CUDA C++ Optimization CUDA C++ Debugging book:
  • Debugging CUDA C++ kernels
  • Tools & techniques
  • Self-testing & reliability
  • Common GPU kernel bugs

Get your copy from Amazon: CUDA C++ Debugging

More AI Research Topics

Read more about: