8 citations · 8 across the 3 of their papers we have counts for
4 papers
Deep Uncertainty-Based Explore for Index Construction and Retrieval in Recommendation System
Xin Jiang, Kaiqiang Wang, Yinlong Wang +7
In recommendation systems, the relevance and novelty of the final results are selected through a cascade system of Matching -> Ranking -> Strategy. The matching model serves as the…
A New Creative Generation Pipeline for Click-Through Rate with Stable Diffusion Model
Hao Yang, Jianxin Yuan, Shuai Yang +3
In online advertising scenario, sellers often create multiple creatives to provide comprehensive demonstrations, making it essential to present the most appealing design to maximiz…
Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertising
Shuai Yang, Hao Yang, Zhuang Zou +3
In the e-commerce advertising scenario, estimating the true probabilities (known as a calibrated estimate) on Click-Through Rate (CTR) and Conversion Rate (CVR) is critical. Previo…
LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee's Advertisement Recommendation
Dang Minh Nguyen, Chenfei Wang, Yan Shen +1
Graph Neural Network (GNN) is the trending solution for item retrieval in recommendation problems. Most recent reports, however, focus heavily on new model architectures. This may…