45 citations · 73 across the 9 of their papers we have counts for
9 papers
Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation
Hengyu Zhang, Chunxu Shen, Xiangguo Sun +5
In real-world recommendation scenarios, users typically engage with platforms through multiple types of behavioral interactions. Multi-behavior recommendation algorithms aim to lev…
Adaptive Graph Integration for Cross-Domain Recommendation via Heterogeneous Graph Coordinators
Hengyu Zhang, Chunxu Shen, Xiangguo Sun +5
In the digital era, users typically interact with diverse items across multiple domains (e.g., e-commerce, streaming platforms, and social networks), generating intricate heterogen…
Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
Qunzhong Wang, Xiangguo Sun, Hong Cheng
In recent years, graph prompting has emerged as a promising research direction, enabling the learning of additional tokens or subgraphs appended to the original graphs without requ…
When LLM Meets Hypergraph: A Sociological Analysis on Personality via Online Social Networks
Zhiyao Shu, Xiangguo Sun, Hong Cheng
Individual personalities significantly influence our perceptions, decisions, and social interactions, which is particularly crucial for gaining insights into human behavior pattern…
ProG: A Graph Prompt Learning Benchmark
Chenyi Zi, Haihong Zhao, Xiangguo Sun +3
Artificial general intelligence on graphs has shown significant advancements across various applications, yet the traditional 'Pre-train & Fine-tune' paradigm faces inefficiencies…
Protein Multimer Structure Prediction via Prompt Learning
Ziqi Gao, Xiangguo Sun, Zijing Liu +3
Understanding the 3D structures of protein multimers is crucial, as they play a vital role in regulating various cellular processes. It has been empirically confirmed that the mult…
All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining
Haihong Zhao, Aochuan Chen, Xiangguo Sun +2
Large Language Models (LLMs) have revolutionized the fields of computer vision (CV) and natural language processing (NLP). One of the most notable advancements of LLMs is that a si…
Counter-Empirical Attacking based on Adversarial Reinforcement Learning for Time-Relevant Scoring System
Xiangguo Sun, Hong Cheng, Hang Dong +3
Scoring systems are commonly seen for platforms in the era of big data. From credit scoring systems in financial services to membership scores in E-commerce shopping platforms, pla…
Graph Prompt Learning: A Comprehensive Survey and Beyond
Xiangguo Sun, Jiawen Zhang, Xixi Wu +3
Artificial General Intelligence (AGI) has revolutionized numerous fields, yet its integration with graph data, a cornerstone in our interconnected world, remains nascent. This pape…