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20232026
most citedMasked Graph Transformer for Large-Scale Recommendation

11 citations · 20 across the 13 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.IR2024★ 1 cited

A Collaborative Ensemble Framework for CTR Prediction

Xiaolong Liu, Zhichen Zeng, Xiaoyi Liu +13

Recent advances in foundation models have established scaling laws that enable the development of larger models to achieve enhanced performance, motivating extensive research into…

cs.LG2024★ 2 cited

F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data

Zexing Xu, Linjun Zhang, Sitan Yang +4

Demand prediction is a crucial task for e-commerce and physical retail businesses, especially during high-stake sales events. However, the limited availability of historical data f…

cs.IR2024★ 2 cited

SimCE: Simplifying Cross-Entropy Loss for Collaborative Filtering

Xiaodong Yang, Huiyuan Chen, Yuchen Yan +5

The learning objective is integral to collaborative filtering systems, where the Bayesian Personalized Ranking (BPR) loss is widely used for learning informative backbones. However…

cs.IR2024★ 11 cited

Masked Graph Transformer for Large-Scale Recommendation

Huiyuan Chen, Zhe Xu, Chin-Chia Michael Yeh +4

Graph Transformers have garnered significant attention for learning graph-structured data, thanks to their superb ability to capture long-range dependencies among nodes. However, t…

cs.LG2024★ 2 cited

Discrete-state Continuous-time Diffusion for Graph Generation

Zhe Xu, Ruizhong Qiu, Yuzhong Chen +6

Graph is a prevalent discrete data structure, whose generation has wide applications such as drug discovery and circuit design. Diffusion generative models, as an emerging research…