3 papers
cs.LG2026
MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches
Xin Wang, Chi Ma, Shaobin Chen +14
Generative recommendation (GR) offers superior modeling capabilities but suffers from prohibitive inference costs due to the repeated encoding of long user histories. While cross-r…
cs.LG2024
Retrofitting Temporal Graph Neural Networks with Transformer
Qiang Huang, Xiao Yan, Xin Wang +5
Temporal graph neural networks (TGNNs) outperform regular GNNs by incorporating time information into graph-based operations. However, TGNNs adopt specialized models (e.g., TGN, TG…
cs.LG2023
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
Qiang Huang, Jiawei Jiang, Xi Susie Rao +10
To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed. Despite the success of these TGN…