WWW 2026 | LLM×Graph论文总结【LLM4Graph Graph4LLM】
WWW 2026将在2026年4月13日到17日于阿联酋迪拜（Dubai, United Arab Emirates）举行。
本文总结了2026 WWW上有关LLM×\times×Graph的相关论文，包含Research一个Track的论文（没有其它track），总计24篇，如有疏漏，欢迎补充。
笔者将LLM和Graph结合的工作分为两大类，一类是LLM4Graph，即LLM做图任务。其中细分了：文本属性图（Text-attributed Graph, TAG）,知识图谱（KG），图基础模型（GFM）。另外一类是利用Graph4LLM，即利用图这种格式来增强LLM的能力。
| LLM4Graph 1. A Graph Foundation Model for Unified Anomaly Detection 2. RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation 3. Disentangled Graph LLM for Molecule Graph Editing under Distribution Shifts 4. Towards Graph Foundation Model: Node Feature Transfer Invariant Modeling on General Graphs 5. Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning 6. Text-attributed Graph Condensation via Text Selection and Attribute Matching 7. Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs 8. UTAG: Leveraging LLM as a Unified Embedding Generator for Text-Attributed Graphs 9. MixRAG : Mixture-of-Experts Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering 10. Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs 11. LLM-enhanced Federated Graph Learning with Geometry-aware Graph Projection and Shared Subspace Aggregation 12. Node Role-Guided LLMs for Dynamic Graph Clustering 13. A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation 14. A Unified Framework for Rule Learning: Integrating Commonsense Knowledge from LLMs with Structured Knowledge from Knowledge Graphs 15. Towards Robust Detection of Chinese Toxic Variants via Dynamic Knowledge Graph–LLM Reasoning 16. Towards Foundation Models for MMKG: Multi-Task Inductive Generalization via Task-Aware Routing 17. Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework 18. RPO-RAG: Aligning Small LLMs with Relation-aware Preference Optimization for Knowledge Graph Question Answering 19. ReaLM: Residual Quantization Bridges Knowledge Graph Embeddings and Large Language Models 20. KG-BiLM: Knowledge Graph Embedding via Bidirectional Language Models 21. VL-KGE: Vision-Language Models Meet Knowledge Graph Embedding Graph4LLM 22. How Human Experts Educate Specialized LLMs: Filling Knowledge Gaps in KG-Augmented Generation through Hallucination Detection 23. FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks 24. MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning |
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1 A Graph Foundation Model for Unified Anomaly Detection
作者：Renda Han, Xiaobao Wang, Luzhi Wang, Wenxin Zhang, Guangzhen Yao and Hongxiang Liang
关键词：异常检测，图基础模型
2 RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation
链接：https://arxiv.org/abs/2601.15124
作者：Haonan Yuan, Qingyun Sun, Jiacheng Tao, Xingcheng Fu and Jianxin Li
关键词：RAG，图基础模型，图提示学习
3 Disentangled Graph LLM for Molecule Graph Editing under Distribution Shifts
作者：Yang Yao, Xin Wang, Yuan Meng, Zeyang Zhang, Hong Mei and Wenwu Zhu
关键词：分子图，分布偏移
4 Towards Graph Foundation Model: Node Feature Transfer Invariant Modeling on General Graphs
作者：Jitao Zhao, Yi Wang, Yawen Li, Dongxiao He, Di Jin, Zhiyong Feng and Weixiong Zhang
关键词：图基础模型，迁移不变性
5 Detecting Miscitation on the Scholarly Web through LLM-Augmented Text-Rich Graph Learning
作者：Huidong Wu, Haojia Xiang, Jingtong Gao, Xiangyu Zhao, Dengsheng Wu and Jianping Li
关键词：错误学术引用，富文本图，LLM
6 Text-attributed Graph Condensation via Text Selection and Attribute Matching
作者：Haowei Han, Yuxiang Wang, Guojia Wan, Hao Wang, Shanshan Feng, Hao Huang, Jiawei Jiang and Xiao Yan
关键词：文本图压缩，属性匹配
7 Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs
作者：Zihui Chen, Yuling Wang, Pengfei Jiao, Kai Wu, Xiao Wang, Xiang Ao and Dalin Zhang
关键词：文本图，对抗攻击，LLM
8 UTAG: Leveraging LLM as a Unified Embedding Generator for Text-Attributed Graphs
作者：Mingqian Ding, Jianjun Li, Zhiyuan Ma, Liwei Zhang and Wenqi Yang
关键词：文本图，嵌入表示，LLM
9 MixRAG : Mixture-of-Experts Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering
链接：https://arxiv.org/abs/2509.21391
作者：Lihui Liu, Jiayuan Ding, Subhabrata Mukherjee and Carl Yang
关键词：文本图问答，RAG
10 Reasoning by Exploration: A Unified Approach to Retrieval and Generation over Graphs
链接：https://arxiv.org/abs/2510.07484
作者：Haoyu Han, Kai Guo, Harry Shomer, Yu Wang, Yucheng Chu, Hang Li, Li Ma and Jiliang Tang
关键词：LLM，RAG，多跳问答
11 LLM-enhanced Federated Graph Learning with Geometry-aware Graph Projection and Shared Subspace Aggregation
作者：Pengyang Zhou, Zhihao Huang, Jiahe Xu, Wu Wen, Xiaolin Zheng, Chaochao Chen and Jianwei Yin
关键词：联邦图学习，LLM
12 Node Role-Guided LLMs for Dynamic Graph Clustering
作者：Dongyuan Li, Ying Zhang, Yaozu Wu and Renhe Jiang
关键词：动态图聚类，LLM
13 A Unified Framework for Context-Aware and Relation-Aware Graph Retrieval-Augmented Generation
作者：Haoyang Zhong, Yifei Sun, Antong Zhang, Chunping Wang, Lei Chen and Yang Yang
关键词：GraphRAG，上下文感知
14 A Unified Framework for Rule Learning: Integrating Commonsense Knowledge from LLMs with Structured Knowledge from Knowledge Graphs
作者：Qirui Hao, Kewei Cheng, Tongze Zhang, Hongyuan Liu, Junming Shao and Carl Yang
关键词：知识图谱，LLM
15 Towards Robust Detection of Chinese Toxic Variants via Dynamic Knowledge Graph–LLM Reasoning
作者：Shaochen Yang, Kefei Zhou and Wei Xu
关键词：动态知识图谱，LLM
16 Towards Foundation Models for MMKG: Multi-Task Inductive Generalization via Task-Aware Routing
作者：Shundong Yang, Jing Yang, Xiaowen Jiang, Xiaofen Wang, Laurence T. Yang, Yuan Gao, Xinfa Jiang, Jie Chen and Chaojun Zhang
关键词：MMKG，多任务，基础模型
17 Towards Open-World Retrieval-Augmented Generation on Knowledge Graph: A Multi-Agent Collaboration Framework
链接：https://arxiv.org/abs/2509.01238
作者：Jiasheng Xu, Mingda Li, Yongqiang Tang, Peijie Wang and Wensheng Zhang
关键词：RAG，LLM，Agent，知识图谱
18 RPO-RAG: Aligning Small LLMs with Relation-aware Preference Optimization for Knowledge Graph Question Answering
链接：https://arxiv.org/abs/2601.19225
作者：Kaehyun Um, Kyuhwan Yeom, Haerim Yang, Minyoung Choi, Hyeongjun Yang and Kyong-Ho Lee
关键词：知识图谱问答，RAG，LLM
19 ReaLM: Residual Quantization Bridges Knowledge Graph Embeddings and Large Language Models
链接：https://arxiv.org/abs/2510.09711
作者：Wenbin Guo, Xin Wang, Jiaoyan Chen, Lingbing Guo, Zhao Li and Zirui Chen
关键词：知识图谱补全，LLM
20 KG-BiLM: Knowledge Graph Embedding via Bidirectional Language Models
链接：https://arxiv.org/abs/2506.03576
作者：Zirui Chen, Xin Wang, Zhao Li, Wenbin Guo, Dongxiao He, Yanbing Li and Wushour Silamu
关键词：知识图谱嵌入，双向LLM
21 VL-KGE: Vision鈥揕anguage Models Meet Knowledge Graph Embedding
作者：Athanasios Efthymiou, Stevan Rudinac, Monika Kackovic, Nachoem Wijnberg and Marcel Worring
关键词：知识图谱嵌入，VLM
22 How Human Experts Educate Specialized LLMs: Filling Knowledge Gaps in KG-Augmented Generation through Hallucination Detection
作者：Chaofan Li, Lixing Chen, Junhua Tang, Yang Bai, Yutong Zhang, Zhi Zheng, Pan Zhou and Zhe Qu
关键词：幻觉检测，知识图谱增强生成
23 FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks
作者：Naen Xu, Jinghuai Zhang, Ping He, Chunyi Zhou, Jun Wang, Zhihui Fu, Tianyu Du, Zhaoxiang Wang and Shouling Ji
关键词：LLM欺诈检测，知识图谱增强
24 MemoTime: Memory-Augmented Temporal Knowledge Graph Enhanced Large Language Model Reasoning
链接：https://arxiv.org/abs/2510.13614
作者：ingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu, Xin Yuan, Liming Zhu and Wenjie Zhang
关键词：时序知识图谱增强推理，LLM，RAG