1
Towards Anomaly Detection on Relational Data
针对关系数据的异常检测新方法，填补图结构数据异常识别空白。
arXiv:2606.18621v1 Announce Type: new Abstract: Relational databases are widely used for managing structured data in real-world systems. Detecting ano…
2
VeriGraph: Towards Verifiable Data-Analytic Agents
大模型数据智能体验证难题新解，VeriGraph用图结构提升分析可信度。
arXiv:2606.16603v1 Announce Type: cross Abstract: LLM-based agents have demonstrated strong capabilities in data-intensive analytical tasks, yet their…
3
TokenMizer: Graph-Structured Session Memory for Long-Horizon LLM Context Management
基于图结构的会话记忆框架，解决LLM长上下文管理难题，提供更高效的长程对话记忆。
arXiv:2606.06337v1 Announce Type: new Abstract: Large language model (LLM) deployments for long-horizon tasks face a fundamental constraint: context w…
4
In-Context Graphical Inference
新的上下文图推理范式，无需参数更新即可在图中实现快速预测与结构归纳。
arXiv:2606.05042v1 Announce Type: cross Abstract: Marginal inference in discrete graphical models forces a choice between exactness and scalability: e…
5
ExpGraph: Model-Agnostic Experience Learning with Graph-Structured Memory for LLM Agents
创新提出图结构记忆让LLM智能体高效积累经验，与模型无关通用性强。
arXiv:2605.30712v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in reasoning, tool use, and multi-ste…
6
Graph-Enhanced Policy Optimization in LLM Agent Training
将图结构融入LLM Agent策略优化，显著提升多步推理和任务完成能力。
arXiv:2510.26270v2 Announce Type: replace Abstract: Multi-step LLM agents in interactive environments represent a crucial step toward long-horizon dec…
7
Graph is a Substrate Across Data Modalities
探讨图结构如何作为多种数据模态的通用基底，ICML26收录的前沿研究。
arXiv:2601.22384v2 Announce Type: replace-cross Abstract: Graphs provide a natural representation of relational structure that arises across diverse d…
8
Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction
融合图结构与Seq2Seq模型，提出GA-S2S框架提升知识图谱链接预测效果，论文亮点突出。
arXiv:2605.18211v1 Announce Type: new Abstract: We introduce Graph-Augmented Sequence-to-Sequence (GA-S2S), a novel framework that integrates a T5-sma…