Unlocking Graph Structure Learning with Tree-Guided Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Zhihan, Li, Xunkai, Zhu, Lei, Zeng, Guang, Fan, Bowen, Wen, Yanzhe, Qin, Hongchao, Li, Rong-Hua, Wang, Guoren |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
by: Li, Xunkai, et al.
Published: (2025)
by: Li, Xunkai, et al.
Published: (2025)
When LLMs meet open-world graph learning: a new perspective for unlabeled data uncertainty
by: Wen, Yanzhe, et al.
Published: (2025)
by: Wen, Yanzhe, et al.
Published: (2025)
Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach
by: Li, Xunkai, et al.
Published: (2025)
by: Li, Xunkai, et al.
Published: (2025)
Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
by: Wu, Xiang, et al.
Published: (2026)
by: Wu, Xiang, et al.
Published: (2026)
LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning
by: Li, Xunkai, et al.
Published: (2026)
by: Li, Xunkai, et al.
Published: (2026)
State Space Models over Directed Graphs
by: She, Junzhi, et al.
Published: (2025)
by: She, Junzhi, et al.
Published: (2025)
Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneity
by: Zhang, Sirui, et al.
Published: (2026)
by: Zhang, Sirui, et al.
Published: (2026)
GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments
by: Du, Enjun, et al.
Published: (2025)
by: Du, Enjun, et al.
Published: (2025)
Rethinking Client-oriented Federated Graph Learning
by: Chen, Zekai, et al.
Published: (2025)
by: Chen, Zekai, et al.
Published: (2025)
Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach
by: Li, Xunkai, et al.
Published: (2025)
by: Li, Xunkai, et al.
Published: (2025)
GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective
by: Wang, Xu, et al.
Published: (2026)
by: Wang, Xu, et al.
Published: (2026)
ScaDyG:A New Paradigm for Large-scale Dynamic Graph Learning
by: Wu, Xiang, et al.
Published: (2025)
by: Wu, Xiang, et al.
Published: (2025)
OpenGU: A Comprehensive Benchmark for Graph Unlearning
by: Fan, Bowen, et al.
Published: (2025)
by: Fan, Bowen, et al.
Published: (2025)
RoleMAG: Learning Neighbor Roles in Multimodal Graphs
by: Zuo, Yilong, et al.
Published: (2026)
by: Zuo, Yilong, et al.
Published: (2026)
CAMPA: Efficient and Aligned Multimodal Graph Learning via Decoupled Propagation and Aggregation
by: Su, Daohan, et al.
Published: (2026)
by: Su, Daohan, et al.
Published: (2026)
DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated Text-Attributed Graphs
by: Chen, Zekai, et al.
Published: (2026)
by: Chen, Zekai, et al.
Published: (2026)
Federated Prototype Graph Learning
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
OpenMAG: A Comprehensive Benchmark for Multimodal-Attributed Graph
by: Wan, Chenxi, et al.
Published: (2026)
by: Wan, Chenxi, et al.
Published: (2026)
Federated Graph Unlearning
by: Ai, Yuming, et al.
Published: (2025)
by: Ai, Yuming, et al.
Published: (2025)
Knowledge-Driven Federated Graph Learning on Model Heterogeneity
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
FedGTA: Topology-aware Averaging for Federated Graph Learning
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach
by: Liu, Sicheng, et al.
Published: (2026)
by: Liu, Sicheng, et al.
Published: (2026)
Towards Unbiased Federated Graph Learning: Label and Topology Perspectives
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
Rethinking Node-wise Propagation for Large-scale Graph Learning
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective
by: Sun, Henan, et al.
Published: (2025)
by: Sun, Henan, et al.
Published: (2025)
BoostFGL: Boosting Fairness in Federated Graph Learning
by: Chen, Zekai, et al.
Published: (2026)
by: Chen, Zekai, et al.
Published: (2026)
Toward General and Robust LLM-enhanced Text-attributed Graph Learning
by: Zhang, Zihao, et al.
Published: (2025)
by: Zhang, Zihao, et al.
Published: (2025)
STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning
by: Chen, Zekai, et al.
Published: (2026)
by: Chen, Zekai, et al.
Published: (2026)
Unveiling the Vulnerability of Graph-LLMs: An Interpretable Multi-Dimensional Adversarial Attack on TAGs
by: Fan, Bowen, et al.
Published: (2025)
by: Fan, Bowen, et al.
Published: (2025)
When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach
by: Zhang, Zhihan, et al.
Published: (2025)
by: Zhang, Zhihan, et al.
Published: (2025)
Towards Data-centric Machine Learning on Directed Graphs: a Survey
by: Sun, Henan, et al.
Published: (2024)
by: Sun, Henan, et al.
Published: (2024)
MM-OpenFGL: A Comprehensive Benchmark for Multimodal Federated Graph Learning
by: Li, Xunkai, et al.
Published: (2026)
by: Li, Xunkai, et al.
Published: (2026)
Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis
by: Zhang, Ru, et al.
Published: (2026)
by: Zhang, Ru, et al.
Published: (2026)
Dual-Tree LLM-Enhanced Negative Sampling for Implicit Collaborative Filtering
by: Wu, Jiayi, et al.
Published: (2026)
by: Wu, Jiayi, et al.
Published: (2026)
Toward General Digraph Contrastive Learning: A Dual Spatial Perspective
by: Su, Daohan, et al.
Published: (2025)
by: Su, Daohan, et al.
Published: (2025)
OptiMAG: Structure-Semantic Alignment via Unbalanced Optimal Transport
by: Zuo, Yilong, et al.
Published: (2026)
by: Zuo, Yilong, et al.
Published: (2026)
FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
OpenDDI: A Comprehensive Benchmark for DDI Prediction
by: Jin, Xinmo, et al.
Published: (2026)
by: Jin, Xinmo, et al.
Published: (2026)
Towards Effective and General Graph Unlearning via Mutual Evolution
by: Li, Xunkai, et al.
Published: (2024)
by: Li, Xunkai, et al.
Published: (2024)
Similar Items
-
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
by: Li, Xunkai, et al.
Published: (2025) -
When LLMs meet open-world graph learning: a new perspective for unlabeled data uncertainty
by: Wen, Yanzhe, et al.
Published: (2025) -
Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach
by: Li, Xunkai, et al.
Published: (2025) -
Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms
by: Wu, Xiang, et al.
Published: (2026) -
LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning
by: Li, Xunkai, et al.
Published: (2026)