Cover Image

Exploring the Potential of Large Language Models as Predictors in Dynamic Text-Attributed Graphs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lei, Runlin, Ji, Jiarui, Ding, Haipeng, Yi, Lu, Wei, Zhewei, Liu, Yongchao, Hong, Chuntao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning
by: Peng, Jie, et al.
Published: (2025)

Robustness in Text-Attributed Graph Learning: Insights, Trade-offs, and New Defenses
by: Lei, Runlin, et al.
Published: (2025)

Rethinking and Benchmarking Large Language Models for Graph Reasoning
by: Hu, Yuwei, et al.
Published: (2025)

Scalable and Accurate Graph Reasoning with LLM-based Multi-Agents
by: Hu, Yuwei, et al.
Published: (2024)

Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level
by: Lei, Runlin, et al.
Published: (2024)

GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
by: Zhu, Yun, et al.
Published: (2024)

GraphGen+: Advancing Distributed Subgraph Generation and Graph Learning On Industrial Graphs
by: Jin, Yue, et al.
Published: (2025)

Distributed Graph Neural Network Inference With Just-In-Time Compilation For Industry-Scale Graphs
by: Wu, Xiabao, et al.
Published: (2025)

GraphRPM: Risk Pattern Mining on Industrial Large Attributed Graphs
by: Tian, Sheng, et al.
Published: (2024)

Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
by: Peng, Jie, et al.
Published: (2024)

Subgraph Retrieval Enhanced by Graph-Text Alignment for Commonsense Question Answering
by: Peng, Boci, et al.
Published: (2024)

Text2GQL-Bench: A Text to Graph Query Language Benchmark [Experiment, Analysis & Benchmark]
by: Lyu, Songlin, et al.
Published: (2026)

Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report
by: Ding, Haipeng, et al.
Published: (2025)

LLM-Based Multi-Agent Systems are Scalable Graph Generative Models
by: Ji, Jiarui, et al.
Published: (2024)

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
by: Chen, Zhikai, et al.
Published: (2023)

UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding
by: Fang, Yi, et al.
Published: (2024)

Exploring the Potential of Large Language Models in Graph Generation
by: Yao, Yang, et al.
Published: (2024)

GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models
by: Fang, Yi, et al.
Published: (2024)

Exploring the Potential of Large Language Models in Fine-Grained Review Comment Classification
by: Nguyen, Linh, et al.
Published: (2025)

Leveraging LLM-based agents for social science research: insights from citation network simulations
by: Ji, Jiarui, et al.
Published: (2025)

Tabular Foundation Models are Strong Graph Anomaly Detectors
by: Liu, Yunhui, et al.
Published: (2026)

Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs
by: Sun, Shengyin, et al.
Published: (2023)

Learning Agent-Compatible Context Management for Long-Horizon Tasks
by: Yi, Lu, et al.
Published: (2026)

Large Language Models Meet Graph Neural Networks for Text-Numeric Graph Reasoning
by: Song, Haoran, et al.
Published: (2025)

Graph Retrieval-Augmented Generation: A Survey
by: Peng, Boci, et al.
Published: (2024)

Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited
by: He, Mingguo, et al.
Published: (2022)

Mitigating Interpretation Bias in Rock Records with Large Language Models: Insights from Paleoenvironmental Analysis
by: Wang, Luoqi, et al.
Published: (2024)

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation
by: He, Chuan, et al.
Published: (2025)

LLM-BI: Towards Fully Automated Bayesian Inference with Large Language Models
by: Huang, Yongchao
Published: (2025)

Exploring the Potential of Large Language Models for Heterophilic Graphs
by: Wu, Yuxia, et al.
Published: (2024)

Text-Graph Synergy: A Bidirectional Verification and Completion Framework for RAG
by: Zhong, Jiarui, et al.
Published: (2026)

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression
by: Di, Zijun, et al.
Published: (2026)

Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs
by: Zhang, Taiyan, et al.
Published: (2024)

Improving Attributed Text Generation of Large Language Models via Preference Learning
by: Li, Dongfang, et al.
Published: (2024)

Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applications
by: Su, Guangxin, et al.
Published: (2025)

Text Steganography with Dynamic Codebook and Multimodal Large Language Model
by: Gao, Jianxin, et al.
Published: (2026)

Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs
by: Chen, Zihui, et al.
Published: (2026)

Unleashing the Potential of Text-attributed Graphs: Automatic Relation Decomposition via Large Language Models
by: Seo, Hyunjin, et al.
Published: (2024)

Future Link Prediction Without Memory or Aggregation
by: Yi, Lu, et al.
Published: (2025)

Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
by: Zhang, Zhongjian, et al.
Published: (2026)