DAGPrompT: Pushing the Limits of Graph Prompting with a Distribution-aware Graph Prompt Tuning Approach
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Qin, Wang, Liang, Zheng, Bo, Song, Guojie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
by: Chen, Qin, et al.
Published: (2025)
by: Chen, Qin, et al.
Published: (2025)
Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022)
by: Fang, Taoran, et al.
Published: (2022)
SGPT: Few-Shot Prompt Tuning for Signed Graphs
by: Zhai, Zian, et al.
Published: (2024)
by: Zhai, Zian, et al.
Published: (2024)
Edge Prompt Tuning for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Urban Region Pre-training and Prompting: A Graph-based Approach
by: Jin, Jiahui, et al.
Published: (2024)
by: Jin, Jiahui, et al.
Published: (2024)
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
EPLKG: Efficient Prompt Learning with Knowledge Graph
by: Lim, YongTaek, et al.
Published: (2023)
by: Lim, YongTaek, et al.
Published: (2023)
Prompt-Driven Continual Graph Learning
by: Wang, Qi, et al.
Published: (2025)
by: Wang, Qi, et al.
Published: (2025)
Event-Aware Prompt Learning for Dynamic Graphs
by: Yu, Xingtong, et al.
Published: (2025)
by: Yu, Xingtong, et al.
Published: (2025)
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
by: Gong, Chenghua, et al.
Published: (2023)
by: Gong, Chenghua, et al.
Published: (2023)
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
A Graph Prompt Fine-Tuning Method for WSN Spatio-Temporal Correlation Anomaly Detection
by: Ye, Miao, et al.
Published: (2026)
by: Ye, Miao, et al.
Published: (2026)
Graph Neural Prompting with Large Language Models
by: Tian, Yijun, et al.
Published: (2023)
by: Tian, Yijun, et al.
Published: (2023)
Causal-aware Graph Neural Architecture Search under Distribution Shifts
by: Li, Peiwen, et al.
Published: (2024)
by: Li, Peiwen, et al.
Published: (2024)
HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
by: Ma, Yihong, et al.
Published: (2023)
by: Ma, Yihong, et al.
Published: (2023)
HGMP:Heterogeneous Graph Multi-Task Prompt Learning
by: Jiao, Pengfei, et al.
Published: (2025)
by: Jiao, Pengfei, et al.
Published: (2025)
Evaluating Generalization and Representation Stability in Small LMs via Prompting, Fine-Tuning and Out-of-Distribution Prompts
by: Raja, Rahul, et al.
Published: (2025)
by: Raja, Rahul, et al.
Published: (2025)
All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)
by: Sun, Xiangguo, et al.
Published: (2024)
by: Sun, Xiangguo, et al.
Published: (2024)
Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
by: Ali, Muhammad Asif, et al.
Published: (2024)
by: Ali, Muhammad Asif, et al.
Published: (2024)
Item Cluster-aware Prompt Learning for Session-based Recommendation
by: Yang, Wooseong, et al.
Published: (2024)
by: Yang, Wooseong, et al.
Published: (2024)
Plug and Play with Prompts: A Prompt Tuning Approach for Controlling Text Generation
by: Ajwani, Rohan Deepak, et al.
Published: (2024)
by: Ajwani, Rohan Deepak, et al.
Published: (2024)
Heterogeneous Graph Prompt Learning via Adaptive Weight Pruning
by: Wei, Chu-Yuan, et al.
Published: (2025)
by: Wei, Chu-Yuan, et al.
Published: (2025)
Prompt-Based Spatio-Temporal Graph Transfer Learning
by: Hu, Junfeng, et al.
Published: (2024)
by: Hu, Junfeng, et al.
Published: (2024)
Graph Your Own Prompt
by: Ding, Xi, et al.
Published: (2025)
by: Ding, Xi, et al.
Published: (2025)
Graphs Generalization under Distribution Shifts
by: Tian, Qin, et al.
Published: (2024)
by: Tian, Qin, et al.
Published: (2024)
Prompt Learning on Temporal Interaction Graphs
by: Chen, Xi, et al.
Published: (2024)
by: Chen, Xi, et al.
Published: (2024)
Selective Prompting Tuning for Personalized Conversations with LLMs
by: Huang, Qiushi, et al.
Published: (2024)
by: Huang, Qiushi, et al.
Published: (2024)
DynaPrompt: Dynamic Test-Time Prompt Tuning
by: Xiao, Zehao, et al.
Published: (2025)
by: Xiao, Zehao, et al.
Published: (2025)
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
by: Zhang, Zheng, et al.
Published: (2024)
by: Zhang, Zheng, et al.
Published: (2024)
Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion
by: Lan, Pengxiang, et al.
Published: (2024)
by: Lan, Pengxiang, et al.
Published: (2024)
Towards Graph Prompt Learning: A Survey and Beyond
by: Long, Qingqing, et al.
Published: (2024)
by: Long, Qingqing, et al.
Published: (2024)
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
by: Wen, Yilin, et al.
Published: (2023)
by: Wen, Yilin, et al.
Published: (2023)
Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
by: Liu, Guojie, et al.
Published: (2026)
by: Liu, Guojie, et al.
Published: (2026)
PGCLODA: Prompt-Guided Graph Contrastive Learning for Oligopeptide-Infectious Disease Association Prediction
by: Tan, Dayu, et al.
Published: (2025)
by: Tan, Dayu, et al.
Published: (2025)
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
by: Choi, Yunseon, et al.
Published: (2024)
by: Choi, Yunseon, et al.
Published: (2024)
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation
by: Jain, Abhinav, et al.
Published: (2024)
by: Jain, Abhinav, et al.
Published: (2024)
DGP: A Dual-Granularity Prompting Framework for Fraud Detection with Graph-Enhanced LLMs
by: Li, Yuan, et al.
Published: (2025)
by: Li, Yuan, et al.
Published: (2025)
FnRGNN: Distribution-aware Fairness in Graph Neural Network
by: Park, Soyoung, et al.
Published: (2025)
by: Park, Soyoung, et al.
Published: (2025)
BadPromptFL: A Novel Backdoor Threat to Prompt-based Federated Learning in Multimodal Models
by: Zhang, Maozhen, et al.
Published: (2025)
by: Zhang, Maozhen, et al.
Published: (2025)
Similar Items
-
Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
by: Chen, Qin, et al.
Published: (2025) -
Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022) -
SGPT: Few-Shot Prompt Tuning for Signed Graphs
by: Zhai, Zian, et al.
Published: (2024) -
Edge Prompt Tuning for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025) -
Urban Region Pre-training and Prompting: A Graph-based Approach
by: Jin, Jiahui, et al.
Published: (2024)