1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples
Xiaoxiao Xu, Hao Wu, Wenhui Yu +3
We propose a general model-agnostic Contrastive learning framework with Counterfactual Samples Synthesizing (CCSS) for modeling the monotonicity between the neural network output a…
An End-to-End Multi-objective Ensemble Ranking Framework for Video Recommendation
Tiantian He, Minzhi Xie, Runtong Li +6
We propose a novel End-to-end Multi-objective Ensemble Ranking framework (EMER) for the multi-objective ensemble ranking module, which is the most critical component of the short v…
Incorporating Group Prior into Variational Inference for Tail-User Behavior Modeling in CTR Prediction
Han Xu, Taoxing Pan, Zhiqiang Liu +2
User behavior modeling -- which aims to extract user interests from behavioral data -- has shown great power in Click-through rate (CTR) prediction, a key component in recommendati…
A Model-based Multi-Agent Personalized Short-Video Recommender System
Peilun Zhou, Xiaoxiao Xu, Lantao Hu +2
Recommender selects and presents top-K items to the user at each online request, and a recommendation session consists of several sequential requests. Formulating a recommendation…