Copertina

CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Feiyang, Zhang, Zhongbao, Ye, Junda, Sun, Li, Qi, Jianzhong
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts
di: Ye, Junda, et al.
Pubblicazione: (2025)

Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces
di: Sun, Li, et al.
Pubblicazione: (2024)

Sample-specific Masks for Visual Reprogramming-based Prompting
di: Cai, Chengyi, et al.
Pubblicazione: (2024)

Prompt-Driven Continual Graph Learning
di: Wang, Qi, et al.
Pubblicazione: (2025)

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk
di: Azizi, Ilia, et al.
Pubblicazione: (2025)

HGPROMPT: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning
di: Yu, Xingtong, et al.
Pubblicazione: (2023)

Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
di: Sun, Li, et al.
Pubblicazione: (2024)

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction
di: Ye, Zesheng, et al.
Pubblicazione: (2025)

Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
di: Sun, Li, et al.
Pubblicazione: (2026)

CLEAR: Can Language Models Really Understand Causal Graphs?
di: Chen, Sirui, et al.
Pubblicazione: (2024)

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
di: Cai, Chengyi, et al.
Pubblicazione: (2025)

Heterogeneous Graph Prompt Learning via Adaptive Weight Pruning
di: Wei, Chu-Yuan, et al.
Pubblicazione: (2025)

HGMP:Heterogeneous Graph Multi-Task Prompt Learning
di: Jiao, Pengfei, et al.
Pubblicazione: (2025)

Instance-Aware Graph Prompt Learning
di: Li, Jiazheng, et al.
Pubblicazione: (2024)

Distributional Inverse Reinforcement Learning
di: Wu, Feiyang, et al.
Pubblicazione: (2025)

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting
di: Wang, Beibei, et al.
Pubblicazione: (2026)

Interpretable Clustering with Adaptive Heterogeneous Causal Structure Learning in Mixed Observational Data
di: Li, Wenrui, et al.
Pubblicazione: (2025)

Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering
di: Shi, Long, et al.
Pubblicazione: (2024)

Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering
di: Liu, Lu, et al.
Pubblicazione: (2025)

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
di: Fu, Xingbo, et al.
Pubblicazione: (2025)

DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing
di: Sun, Li, et al.
Pubblicazione: (2024)

HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning
di: Zhu, Qiuyu, et al.
Pubblicazione: (2024)

DDIPrompt: Drug-Drug Interaction Event Prediction based on Graph Prompt Learning
di: Wang, Yingying, et al.
Pubblicazione: (2024)

CLEAR: Unlearning Spurious Style-Content Associations with Contrastive LEarning with Anti-contrastive Regularization
di: Sun, Minghui, et al.
Pubblicazione: (2025)

CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts
di: Li, Peiyuan, et al.
Pubblicazione: (2026)

Single-cell Curriculum Learning-based Deep Graph Embedding Clustering
di: Li, Huifa, et al.
Pubblicazione: (2024)

Item Cluster-aware Prompt Learning for Session-based Recommendation
di: Yang, Wooseong, et al.
Pubblicazione: (2024)

FlexiReg: Flexible Urban Region Representation Learning
di: Sun, Fengze, et al.
Pubblicazione: (2025)

When Prompting Meets Spiking: Graph Sparse Prompting via Spiking Graph Prompt Learning
di: Jiang, Bo, et al.
Pubblicazione: (2026)

Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
di: Sun, Li, et al.
Pubblicazione: (2026)

Structure-enhanced Contrastive Learning for Graph Clustering
di: Wu, Xunlian, et al.
Pubblicazione: (2024)

ProG: A Graph Prompt Learning Benchmark
di: Zi, Chenyi, et al.
Pubblicazione: (2024)

HERO: Heterogeneous Continual Graph Learning via Meta-Knowledge Distillation
di: Sun, Guiquan, et al.
Pubblicazione: (2025)

A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
di: Du, Honglin, et al.
Pubblicazione: (2026)

From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited
di: Wang, Zheng, et al.
Pubblicazione: (2023)

FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
di: Luo, Renqiang, et al.
Pubblicazione: (2024)

Disentangled Graph Prompting for Out-Of-Distribution Detection
di: Yang, Cheng, et al.
Pubblicazione: (2026)

Urban Region Pre-training and Prompting: A Graph-based Approach
di: Jin, Jiahui, et al.
Pubblicazione: (2024)

Federated Graph Learning for Cross-Domain Recommendation
di: Yang, Ziqi, et al.
Pubblicazione: (2024)

LLM-Empowered Class Imbalanced Graph Prompt Learning for Online Drug Trafficking Detection
di: Ma, Tianyi, et al.
Pubblicazione: (2025)