6 papers
End-to-End Semantic ID Generation for Generative Advertisement Recommendation
Jie Jiang, Xinxun Zhang, Enming Zhang +8
Generative Recommendation (GR) has excelled by framing recommendation as next-token prediction. This paradigm relies on Semantic IDs (SIDs) to tokenize large-scale items into discr…
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…
SCoTER: Structured Chain-of-Thought Transfer for Enhanced Recommendation
Jie Jiang, Yang Wu, Qian Li +7
Harnessing the reasoning power of Large Language Models (LLMs) for recommender systems is hindered by two fundamental challenges. First, current approaches lack a mechanism for aut…
Spend Search Where It Pays: Value-Guided Structured Sampling and Optimization for Generative Recommendation
Jie Jiang, Yangru Huang, Zeyu Wang +4
Generative recommendation via autoregressive models has unified retrieval and ranking into a single conditional generation framework. However, fine-tuning these models with Reinfor…
DiffuReason: Bridging Latent Reasoning and Generative Refinement for Sequential Recommendation
Jie Jiang, Yang Wu, Qian Li +6
Latent reasoning has emerged as a promising paradigm for sequential recommendation, enabling models to capture complex user intent through multi-step deliberation. Yet existing app…
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…