6 papers
UniVA: Unified Value Alignment for Generative Recommendation in Online Advertising at Tencent
Xinxun Zhang, Yuling Xiong, Jiale Zhou +14
Generative Recommendation (GR) reformulates recommendation as next-token generation over item Semantic IDs (SIDs) and has shown promise in industrial applications. However, extendi…
OneRanker: Unified Generation and Ranking with One Model in Industrial Advertising Recommendation
Dekai Sun, Yiming Liu, Jiafan Zhou +6
The end-to-end generative paradigm is revolutionizing advertising recommendation systems, driving a shift from traditional cascaded architectures towards unified modeling. However,…
RELATE: A Reinforcement Learning-Enhanced LLM Framework for Advertising Text Generation
Jinfang Wang, Jiajie Liu, Jianwei Wu +8
In online advertising, advertising text plays a critical role in attracting user engagement and driving advertiser value. Existing industrial systems typically follow a two-stage p…
GPR: Towards a Generative Pre-trained One-Model Paradigm for Large-Scale Advertising Recommendation
Jun Zhang, Yi Li, Yue Liu +19
As an intelligent infrastructure connecting users with commercial content, advertising recommendation systems play a central role in information flow and value creation within the…
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…
Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations
Yuhao Yang, Zhi Ji, Zhaopeng Li +8
Generative models have recently gained attention in recommendation systems by directly predicting item identifiers from user interaction sequences. However, existing methods suffer…