Copertina

Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gong, Chenghua, Li, Xiang, Yu, Jianxiang, Yao, Cheng, Tan, Jiaqi, Yu, Chengcheng
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
di: Gong, Chenghua, et al.
Pubblicazione: (2024)

Edge Prompt Tuning for Graph Neural Networks
di: Fu, Xingbo, et al.
Pubblicazione: (2025)

Universal Prompt Tuning for Graph Neural Networks
di: Fang, Taoran, et al.
Pubblicazione: (2022)

Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs
di: Yu, Jianxiang, et al.
Pubblicazione: (2023)

RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning
di: Zhu, Jiapeng, et al.
Pubblicazione: (2024)

Commute Graph Neural Networks
di: Zhuo, Wei, et al.
Pubblicazione: (2024)

Do Neural Scaling Laws Exist on Graph Self-Supervised Learning?
di: Ma, Qian, et al.
Pubblicazione: (2024)

HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
di: Ma, Yihong, et al.
Pubblicazione: (2023)

SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
di: Zhu, Yushan, et al.
Pubblicazione: (2024)

Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction
di: Yu, Leisheng, et al.
Pubblicazione: (2025)

All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)
di: Sun, Xiangguo, et al.
Pubblicazione: (2024)

A Comprehensive Survey on Self-Interpretable Neural Networks
di: Ji, Yang, et al.
Pubblicazione: (2025)

GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
di: Fu, Xingbo, et al.
Pubblicazione: (2025)

Towards Few-shot Self-explaining Graph Neural Networks
di: Peng, Jingyu, et al.
Pubblicazione: (2024)

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting
di: Wu, Lirong, et al.
Pubblicazione: (2024)

Learning Diverse Policies with Soft Self-Generated Guidance
di: Wang, Guojian, et al.
Pubblicazione: (2024)

Self-Distilled Disentangled Learning for Counterfactual Prediction
di: Li, Xinshu, et al.
Pubblicazione: (2024)

GraphRCG: Self-Conditioned Graph Generation
di: Wang, Song, et al.
Pubblicazione: (2024)

Self-Supervised Prompt Optimization
di: Xiang, Jinyu, et al.
Pubblicazione: (2025)

SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
di: Fang, Lanting, et al.
Pubblicazione: (2024)

SONG: Self-Organizing Neural Graphs
di: Struski, Łukasz, et al.
Pubblicazione: (2021)

Spectro-Riemannian Graph Neural Networks
di: Grover, Karish, et al.
Pubblicazione: (2025)

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
di: Zheng, Zinan, et al.
Pubblicazione: (2024)

Self-Compressing Neural Networks
di: Cséfalvay, Szabolcs, et al.
Pubblicazione: (2023)

Aligning Findings with Diagnosis: A Self-Consistent Reinforcement Learning Framework for Trustworthy Radiology Reporting
di: Zhao, Kun, et al.
Pubblicazione: (2026)

A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning
di: Zhou, Zhi, et al.
Pubblicazione: (2025)

MASPOB: Bandit-Based Prompt Optimization for Multi-Agent Systems with Graph Neural Networks
di: Hong, Zhi, et al.
Pubblicazione: (2026)

Enhancing Graph Self-Supervised Learning with Graph Interplay
di: Zhao, Xinjian, et al.
Pubblicazione: (2024)

Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
di: Lv, Jiaqi, et al.
Pubblicazione: (2026)

Towards Faithful Class-level Self-explainability in Graph Neural Networks by Subgraph Dependencies
di: Liu, Fanzhen, et al.
Pubblicazione: (2025)

LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
di: Qiao, Yiran, et al.
Pubblicazione: (2024)

HyboWaveNet: Hyperbolic Graph Neural Networks with Multi-Scale Wavelet Transform for Protein-Protein Interaction Prediction
di: Yu, Qingzhi, et al.
Pubblicazione: (2025)

From Generic Correlation to Input-Specific Credit in On-Policy Self Distillation
di: Shen, Guobin, et al.
Pubblicazione: (2026)

Boolean Product Graph Neural Networks
di: Wang, Ziyan, et al.
Pubblicazione: (2024)

Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data
di: Wang, Zhenzhong, et al.
Pubblicazione: (2024)

Self-Evolving LLMs via Continual Instruction Tuning
di: Kang, Jiazheng, et al.
Pubblicazione: (2025)

Factor Graph-based Interpretable Neural Networks
di: Li, Yicong, et al.
Pubblicazione: (2025)

DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
di: Chen, Qin, et al.
Pubblicazione: (2025)

Epi$^2$-Net: Advancing Epidemic Dynamics Forecasting with Physics-Inspired Neural Networks
di: Sun, Rui, et al.
Pubblicazione: (2025)

DGP: A Dual-Granularity Prompting Framework for Fraud Detection with Graph-Enhanced LLMs
di: Li, Yuan, et al.
Pubblicazione: (2025)