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Graph2text or Graph2token: A Perspective of Large Language Models for Graph Learning

S Yu, Y Wang, R Li, G Liu, Y Shen, S Ji, B Li… - arxiv preprint arxiv …, 2025 - arxiv.org

Graphs are data structures used to represent irregular networks and are prevalent in
numerous real-world applications. Previous methods directly model graph structures and …

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[HTML][HTML] Intelligent Path Planning for UAV Patrolling in Dynamic Environments Based on the Transformer Architecture

CH Yu, J Tsai, YT Chang - Electronics, 2024 - mdpi.com

Due to its NP-Hard property, the Travelling Salesman Problem (TSP) has long been a
prominent research topic in path planning. The goal is to design the algorithm with the …

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Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning

G Su, Y Zhu, W Zhang, H Wang, Y Zhang - arxiv preprint arxiv …, 2024 - arxiv.org

Graph representation learning, involving both node features and graph structures, is crucial
for real-world applications but often encounters pervasive noise. State-of-the-art methods …

LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model

T Lin, P Yan, K Song, Z Jiang, Y Kang, J Lin… - arxiv preprint arxiv …, 2024 - arxiv.org

Graph foundation models (GFMs) have recently gained significant attention. However, the
unique data processing and evaluation setups employed by different studies hinder a …

Path-LLM: A Shortest-Path-based LLM Learning for Unified Graph Representation

W Shang, X Zhu, X Huang - arxiv preprint arxiv:2408.05456, 2024 - arxiv.org

Unified graph representation learning aims to produce node embeddings, which can be
applied to multiple downstream applications. However, existing studies based on graph …