9 citations · 17 across the 22 of their papers we have counts for
6 papers · 1 filter
UniRank: Benchmarking Ranking Models for Unified Sequential Modeling and Feature Interaction
Honghao Li, Xianquan Wang, Zibin Zhang +3
Ranking is a core stage in online advertising and recommender systems. Modern ranking models increasingly unify sequential modeling and feature interaction, yet many advances rely…
ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems
Yi Zhang, Yiwen Zhang, Kai Zheng +2
The remarkable text understanding and generation capabilities of large language models (LLMs) have revitalized the field of general recommendation based on implicit user feedback.…
FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost
Chenhao Feng, Haoli Zhang, Shakhzod Ali-Zade +17
Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, subsequently generating predictio…
Disagreement as Signals: Dual-view Calibration for Sequential Recommendation Denoising
Sijia Li, Min Gao, Zongwei Wang +3
Sequential recommendation seeks to model the evolution of user interests by capturing temporal user intent and item-level transition patterns. Transformer-based recommenders demons…
MASS: Mesh-inellipse Aligned Deformable Surfel Splatting for Hand Reconstruction and Rendering from Egocentric Monocular Video
Haoyu Zhu, Yi Zhang, Lei Yao +2
Reconstructing high-fidelity 3D hands from egocentric monocular videos remains a challenge due to the limitations in capturing high-resolution geometry, hand-object interactions, a…
Efficient Sequential Recommendation for Long Term User Interest Via Personalization
Qiang Zhang, Hanchao Yu, Ivan Ji +14
Recent years have witnessed success of sequential modeling, generative recommender, and large language model for recommendation. Though the scaling law has been validated for seque…