14 citations · 16 across the 7 of their papers we have counts for
7 papers
Generative Recommendation for Large-Scale Advertising
Ben Xue, Dan Liu, Lixiang Wang +27
Generative recommendation has recently attracted widespread attention in industry due to its potential for scaling and stronger model capacity. However, deploying real-time generat…
Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach
Chunxu Zhang, Guodong Long, Hongkuan Guo +5
Multifaceted user modeling aims to uncover fine-grained patterns and learn representations from user data, revealing their diverse interests and characteristics, such as profile, p…
RecFlow: An Industrial Full Flow Recommendation Dataset
Qi Liu, Kai Zheng, Rui Huang +15
Industrial recommendation systems (RS) rely on the multi-stage pipeline to balance effectiveness and efficiency when delivering items from a vast corpus to users. Existing RS bench…
DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models
Wuchao Li, Rui Huang, Haijun Zhao +10
Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary historical interactions. A…
Contextual Distillation Model for Diversified Recommendation
Fan Li, Xu Si, Shisong Tang +6
The diversity of recommendation is equally crucial as accuracy in improving user experience. Existing studies, e.g., Determinantal Point Process (DPP) and Maximal Marginal Relevanc…
Federated Adaptation for Foundation Model-based Recommendations
Chunxu Zhang, Guodong Long, Hongkuan Guo +7
With the recent success of large language models, particularly foundation models with generalization abilities, applying foundation models for recommendations becomes a new paradig…
End-to-end training of Multimodal Model and ranking Model
Xiuqi Deng, Lu Xu, Xiyao Li +10
Traditional recommender systems heavily rely on ID features, which often encounter challenges related to cold-start and generalization. Modeling pre-extracted content features can…