SIGIR 2026 | LLM × Graph论文总结(图增强LLM,GraphRAG,Agent,多模态,知识图谱,搜索,推

SIGIR 2026将在2026年7月20日至24日于澳大利亚墨尔本(Melbourne | Naarm, Australia )举行。

本文总结了SIGIR 2026上有关时空数据(Spatial-Temporal)的相关论文。

按照官网的命名方式,总共有如下4类paper类型:

  • fp\] Full research papers (234 accepted),本文涉及11篇

  • ip\] Industry papers (131 accepted),本文涉及2篇

录用列表https://sigir2026.org/en-AU/pages/program/accepted-papers

LLM × Graph Topic:图增强的LLM,GraphRAG,Agent,多模态,知识图谱,搜索,推荐等。

1. [FP] Verbalizing LightGCN: Direct Learning of Textual Representations from User-Item Interaction Graph via LLMs 2. [FP] DCGL: Dual-Channel Graph Learning with Large Language Models for Knowledge-Aware Recommendation 3. [FP] SSR: Structured Subgraph Retrieval for Temporal Knowledge Graph Question Answering with LLMs 4. [FP] Exploration-and-Thinking: Agentic Reasoning over Knowledge Graphs via an LLM-RL Synergized Framework 5. [FP] MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendation 6. [FP] Robust Multimodal Recommendation via Graph Retrieval-Enhanced Modality Completion 7. [FP]ACE: Semantically-Grounded Graph Alignment via Affective Contrastive Learning 8. [FP] Learning Noise-Resilient and Transferable Graph-Text Alignment via Dynamic Quality Assessment 9. [FP] One-for-All Community Search on Unseen Graphs 10. [FP] Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation 11. [FP] mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA 12. [IP] Efficient LLM Adaptation for Opinion Knowledge Graph Construction: Lessons from the Telecom Industry 13. [IP] From Unstructured to Structured: LLM-Guided Attribute Graphs for Entity Search and Ranking 14. [LRE] Graph-Enhanced Sentence Retrieval for Multi-Document Summarization in Low-Resource Languages 15. [SP] A Graph-Enhanced MLLM for Hierarchical Multimodal Emotion Understanding and Support in Conversations 16. [SP] StAR: Adaptive Structure-Aware Reranking for Semantic-Structural Alignment in GraphRAG

1 [FP] Verbalizing LightGCN: Direct Learning of Textual Representations from User-Item Interaction Graph via LLMs

作者:Manh Khanh Huu Ngo, Hady W. Lauw

关键词:lightgcn,用户-物品交互图,LLM

2 [FP] DCGL: Dual-Channel Graph Learning with Large Language Models for Knowledge-Aware Recommendation

作者:Xinchi Zou, Tongzhenzhi Su, Jianjun Li, Yuan Fu, Chang Liu, Zhiying Deng, Zhiwei Shen

关键词:LLM,图学习,知识感知推荐

3 [FP] SSR: Structured Subgraph Retrieval for Temporal Knowledge Graph Question Answering with LLMs

作者:Ying Zhang, Li Zhang, Wenya Guo, Shilong Ping, Xinying Qian

关键词:时序知识图谱问答,LLM

4 [FP] Exploration-and-Thinking: Agentic Reasoning over Knowledge Graphs via an LLM-RL Synergized Framework

作者:Yi Xia, Gang Zhou, Jing Chen, Xiaohui Chen, Qinlong Fan, Shunhang Li

关键词:智能体推理,知识图谱,强化学习

5 [FP] MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendation

链接 :++https://arxiv.org/abs/2508.15304++

作者:Yuzhuo Dang, Xin Zhang, Zhiqiang Pan, Yuxiao Duan, Wanyu Chen, Fei Cai, Honghui Chen

关键词:多模态推荐,图细化,多模态大模型

6 [FP] Robust Multimodal Recommendation via Graph Retrieval-Enhanced Modality Completion

作者:Yuan Li, Jun Hu, Jiaxin Jiang, Bryan Hooi, Bingsheng He

关键词:多模态推荐,GraphRAG,模态补全

7 [FP] ACE: Semantically-Grounded Graph Alignment via Affective Contrastive Learning

作者:Potito Aghilar, Sabino Roccotelli, Vito Walter Anelli, Alejandro Bellogin, Michelantonio Trizio, Tommaso Di Noia

关键词:图对比学习,LLM

8 [FP] Learning Noise-Resilient and Transferable Graph-Text Alignment via Dynamic Quality Assessment

链接 :++https://arxiv.org/abs/2510.19384++

作者:Mo Li, Zhaosong Zhao, Linlin Ding, Renata Borovica-Gajic, Zhongming Yao, Jianxin Li

关键词:多模态图学习,图基础模型

作者:Yuhang Liu, Minglai Shao, Zengyi Wo, Yunlong Chu, Bing Hao, Shengzhong Liu, Ruijie Wang, Jianxin Li

关键词:社区搜索

10 [FP] Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation

作者:Yuchen Yan, Peiyan Zhang, Zhihua Liu, Hao Wang, Yatao Bian, Weiming Li, Xiaoshuai Hao

关键词:多跳RAG,问题感知的图学习

11 [FP] mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA

链接 :++https://arxiv.org/abs/2508.05318++

作者:Xu Yuan, Liang-Bo Ning, Qingqing Ye, Wenqi Fan, Li Qing

关键词:多模态知识图谱,视觉问答,GraphRAG

12 [IP] Efficient LLM Adaptation for Opinion Knowledge Graph Construction: Lessons from the Telecom Industry

作者:Nai-Chi Yang, Yu-Ming Hsieh, Wei-Yun Ma, Kuo-Wei Chang

关键词:知识图谱构建,LLM

作者:Yilun Zhu, Nikhita Vedula, Shervin Malmasi

关键词:搜索,排序,属性图

14 [LRE] Graph-Enhanced Sentence Retrieval for Multi-Document Summarization in Low-Resource Languages

作者:Xuan-Hung Le, Thi Toan Do, Hoang-Quynh Le

关键词:句子检索,图增强

15 [SP] A Graph-Enhanced MLLM for Hierarchical Multimodal Emotion Understanding and Support in Conversations

作者:Geng Tu, Taiyu Niu, Xi Zeng, Ruifeng Xu, Min Zhang

关键词:情感理解,图增强

16 [SP] StAR: Adaptive Structure-Aware Reranking for Semantic-Structural Alignment in GraphRAG

作者:Junghyun Oh, Sungsu Lim

关键词:重排,GraphRAG

相关推荐
lizhihai_991 小时前
股市学习心得—半导体12种核心材料
大数据·人工智能·学习
FreakStudio1 小时前
MicroPython 内核开发者直接狂喜!这个 Claude 插件市场,把开发全流程做成了「对话式外挂」
python·单片机·嵌入式·面向对象·并行计算·电子diy
研究点啥好呢1 小时前
快手产品经理面试题精选:10道高频考题+答案解析
人工智能·面试·产品经理
流年似水~1 小时前
脚本策划:拍之前先想清楚要剪什么
人工智能·程序人生·语言模型·ai编程
郑寿昌1 小时前
思维链三步法:让AI像人类一样推理
人工智能
圣殿骑士-Khtangc1 小时前
AI Agent架构演进与三层安全防御体系深度解析
人工智能
ZGi.ai2 小时前
智能客服系统设计:从工单分类到自动派单的工程实现
大数据·人工智能·分类
老陈说编程2 小时前
12. LangChain 6大核心调用方法:invoke/stream/batch同步异步全解析,新手也能轻松学会
开发语言·人工智能·python·深度学习·机器学习·ai·langchain
给自己做减法2 小时前
rag混合检索
人工智能·python·rag