41 citations · 41 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Riemannian Graph Tokenizer for Structural Knowledge Transfer
Qimin Zhou, Haibo Liu, Yujie Wang +2
Foundation models are at the forefront of artificial intelligence. A tokenizer, converting the raw input into discrete representations that the model can understand, plays an impor…
cs.LG2026
Data-centric Prompt Tuning for Dynamic Graphs
Yufei Peng, Cheng Yang, Zhengjie Fan +1
Dynamic graphs have attracted increasing attention due to their ability to model complex and evolving relationships in real-world scenarios. Traditional approaches typically pre-tr…
cs.LG2023★ 41 cited
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
Bo Yan, Yang Cao, Haoyu Wang +3
The heterogeneous information network (HIN), which contains rich semantics depicted by meta-paths, has emerged as a potent tool for mitigating data sparsity in recommender systems.…