Image de couverture de livre

GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chu, Xu, Xue, Hanlin, Tan, Zhijie, Wang, Bingce, Mo, Tong, Li, Weiping
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning
par: Chu, Xu, et autres
Publié: (2025)

Domaino1s: Guiding LLM Reasoning for Explainable Answers in High-Stakes Domains
par: Chu, Xu, et autres
Publié: (2025)

Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization
par: Chu, Xu, et autres
Publié: (2026)

Order Matters: Exploring Order Sensitivity in Multimodal Large Language Models
par: Tan, Zhijie, et autres
Publié: (2024)

How to Use Graph Data in the Wild to Help Graph Anomaly Detection?
par: Cao, Yuxuan, et autres
Publié: (2025)

Qwen Look Again: Guiding Vision-Language Reasoning Models to Re-attention Visual Information
par: Chu, Xu, et autres
Publié: (2025)

What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs
par: Fu, Dongqi, et autres
Publié: (2024)

Mitigating Hallucinations on Object Attributes using Multiview Images and Negative Instructions
par: Tan, Zhijie, et autres
Publié: (2025)

When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expected
par: Xu, Haotian, et autres
Publié: (2025)

Kernel Alignment-based Multi-view Unsupervised Feature Selection with Sample-level Adaptive Graph Learning
par: Tan, Yalan, et autres
Publié: (2026)

The Importance of Model Inspection for Better Understanding Performance Characteristics of Graph Neural Networks
par: Shehata, Nairouz, et autres
Publié: (2024)

Similarity-based Neighbor Selection for Graph LLMs
par: Li, Rui, et autres
Publié: (2024)

Tri-Learn Graph Fusion Network for Attributed Graph Clustering
par: Li, Binxiong, et autres
Publié: (2025)

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design
par: Sun, Yuanfu, et autres
Publié: (2025)

Mitigating Label Noise on Graph via Topological Sample Selection
par: Wu, Yuhao, et autres
Publié: (2024)

Graph Propagation Transformer for Graph Representation Learning
par: Chen, Zhe, et autres
Publié: (2023)

Graph Data Selection for Domain Adaptation: A Model-Free Approach
par: Li, Ting-Wei, et autres
Publié: (2025)

GRAFT: Graph-Tokenized LLMs for Tool Planning
par: Gao, Xinyi, et autres
Publié: (2026)

DRGW: Learning Disentangled Representations for Robust Graph Watermarking
par: Li, Jiasen, et autres
Publié: (2026)

Graph Condensation for Open-World Graph Learning
par: Gao, Xinyi, et autres
Publié: (2024)

Graph Random Walk with Feature-Label Space Alignment: A Multi-Label Feature Selection Method
par: Gao, Wanfu, et autres
Publié: (2025)

Understanding When Graph Convolutional Networks Help: A Diagnostic Study on Label Scarcity and Structural Properties
par: Subedi, Nischal, et autres
Publié: (2025)

Graph Homophily Booster: Rethinking the Role of Discrete Features on Heterophilic Graphs
par: Qiu, Ruizhong, et autres
Publié: (2025)

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs
par: Cai, Hanlin, et autres
Publié: (2026)

Understanding Heterophily for Graph Neural Networks
par: Wang, Junfu, et autres
Publié: (2024)

Are LLMs Better GNN Helpers? Rethinking Robust Graph Learning under Deficiencies with Iterative Refinement
par: Wang, Zhaoyan, et autres
Publié: (2025)

SamGoG: A Sampling-Based Graph-of-Graphs Framework for Imbalanced Graph Classification
par: Wang, Shangyou, et autres
Publié: (2025)

GraphRCG: Self-Conditioned Graph Generation
par: Wang, Song, et autres
Publié: (2024)

Double-Diffusion: ODE-Prior Accelerated Diffusion Models for Spatio-Temporal Graph Forecasting
par: Dong, Hanlin, et autres
Publié: (2025)

Adaptive Graph Mixture of Residual Experts: Unsupervised Learning on Diverse Graphs with Heterogeneous Specialization
par: Chu, Yunlong, et autres
Publié: (2025)

Efficient Graph Understanding with LLMs via Structured Context Injection
par: Waghmare, Govind, et autres
Publié: (2025)

Better Not to Propagate: Understanding Edge Uncertainty and Over-smoothing in Signed Graph Neural Networks
par: Choi, Yoonhyuk, et autres
Publié: (2024)

SteinGen: Generating Fidelitous and Diverse Graph Samples
par: Reinert, Gesine, et autres
Publié: (2024)

Distributed-Order Fractional Graph Operating Network
par: Zhao, Kai, et autres
Publié: (2024)

GraphFM: A Comprehensive Benchmark for Graph Foundation Model
par: Xu, Yuhao, et autres
Publié: (2024)

AS-GCL: Asymmetric Spectral Augmentation on Graph Contrastive Learning
par: Liu, Ruyue, et autres
Publié: (2025)

Better Call Graphs: A New Dataset of Function Call Graphs for Malware Classification
par: Hossain, Jakir, et autres
Publié: (2025)

Can LLMs Convert Graphs to Text-Attributed Graphs?
par: Wang, Zehong, et autres
Publié: (2024)

Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding
par: Hu, Bozhen, et autres
Publié: (2024)

LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
par: Du, Lin, et autres
Publié: (2025)