4 papers · 1 filter
RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems
Jin Chen, Shangyu Zhang, Bin Hu +16
The scaling laws for recommender systems have been increasingly validated, where MetaFormer-based architectures consistently benefit from increased model depth, hidden dimensionali…
Tencent Advertising Algorithm Challenge 2025: All-Modality Generative Recommendation
Junwei Pan, Wei Xue, Chao Zhou +20
Generative recommender systems are rapidly emerging as a new paradigm for recommendation, where collaborative identifiers and/or multi-modal content are mapped into discrete token…
HIT Model: A Hierarchical Interaction-Enhanced Two-Tower Model for Pre-Ranking Systems
Haoqiang Yang, Congde Yuan, Kun Bai +3
Online display advertising platforms rely on pre-ranking systems to efficiently filter and prioritize candidate ads from large corpora, balancing relevance to users with strict com…
LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender System
Fengxin Li, Yi Li, Yue Liu +11
Display advertising provides significant value to advertisers, publishers, and users. Traditional display advertising systems utilize a multi-stage architecture consisting of retri…