Cover Image

Learning and Editing Universal Graph Prompt Tuning via Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Jinfeng, Chen, Zheyu, Yang, Shuo, Li, Jinze, Wang, Hewei, Li, Yijie, Ngai, Edith C. H.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-modal Dynamic Proxy Learning for Personalized Multiple Clustering
by: Xu, Jinfeng, et al.
Published: (2025)

MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation
by: Xu, Jinfeng, et al.
Published: (2024)

AlignGroup: Learning and Aligning Group Consensus with Member Preferences for Group Recommendation
by: Xu, Jinfeng, et al.
Published: (2024)

NLGCL: Naturally Existing Neighbor Layers Graph Contrastive Learning for Recommendation
by: Xu, Jinfeng, et al.
Published: (2025)

The Best is Yet to Come: Graph Convolution in the Testing Phase for Multimodal Recommendation
by: Xu, Jinfeng, et al.
Published: (2025)

MDVT: Enhancing Multimodal Recommendation with Model-Agnostic Multimodal-Driven Virtual Triplets
by: Xu, Jinfeng, et al.
Published: (2025)

CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation
by: Xu, Jinfeng, et al.
Published: (2026)

VI-MMRec: Similarity-Aware Training Cost-free Virtual User-Item Interactions for Multimodal Recommendation
by: Xu, Jinfeng, et al.
Published: (2025)

RAINER: A Robust Ensemble Learning Grid Search-Tuned Framework for Rainfall Patterns Prediction
by: Li, Zhenqi, et al.
Published: (2025)

Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
by: Xu, Jinfeng, et al.
Published: (2024)

Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation
by: Xu, Jinfeng, et al.
Published: (2026)

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

DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification
by: Chen, Jian, et al.
Published: (2026)

Exploiting Features and Logits in Heterogeneous Federated Learning
by: Chan, Yun-Hin, et al.
Published: (2022)

Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
by: Yang, Shuo, et al.
Published: (2025)

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

A Survey on Multimodal Recommender Systems: Recent Advances and Future Directions
by: Xu, Jinfeng, et al.
Published: (2025)

On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs
by: Ye, Rongguang, et al.
Published: (2025)

Hypercomplex Prompt-aware Multimodal Recommendation
by: Chen, Zheyu, et al.
Published: (2025)

Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding
by: Li, Jinze, et al.
Published: (2025)

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
by: Zhang, Zheyu, et al.
Published: (2025)

FedIN: Federated Intermediate Layers Learning for Model Heterogeneity
by: Chan, Yun-Hin, et al.
Published: (2023)

MoST: Efficient Monarch Sparse Tuning for 3D Representation Learning
by: Han, Xu, et al.
Published: (2025)

Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs
by: Yang, Shuo, et al.
Published: (2025)

Understanding Prompt Tuning and In-Context Learning via Meta-Learning
by: Genewein, Tim, et al.
Published: (2025)

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

Deep Reinforcement Learning for Ranking Utility Tuning in the Ad Recommender System at Pinterest
by: Yang, Xiao, et al.
Published: (2025)

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

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

WST: Weak-to-Strong Knowledge Transfer via Reinforcement Learning
by: Ge, Haosen, et al.
Published: (2025)

Learning to Inject: Automated Prompt Injection via Reinforcement Learning
by: Chen, Xin, et al.
Published: (2026)

Evolutionary System Prompt Learning for Reinforcement Learning in LLMs
by: Zhang, Lunjun, et al.
Published: (2026)

Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
by: Chan, Yun-Hin, et al.
Published: (2023)

Synergizing Foundation Models and Federated Learning: A Survey
by: Li, Shenghui, et al.
Published: (2024)

CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs
by: Wang, Feiyang, et al.
Published: (2025)

Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
by: Ren, Li, et al.
Published: (2024)

Data-centric Prompt Tuning for Dynamic Graphs
by: Peng, Yufei, et al.
Published: (2026)

Off-Policy Value-Based Reinforcement Learning for Large Language Models
by: Wang, Peng-Yuan, et al.
Published: (2026)

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

Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
by: Ye, Tiandi, et al.
Published: (2025)