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TAGR: Temporally Adaptive Generative Recommendation for Industrial Live-Streaming Advertising
Wencai Ye, Guangyi Liu, Chaoyi Wang +7
Live-streaming advertising is an important monetization channel on short-video and e-commerce platforms, where rapidly changing live content, promoted products, and user feedback i…
From a Static Multi-Level Small Semantic Codebook to a Dynamic Single-Level Large Semantic Codebook for Generative Recommendation
Tianlu Xie, Xin Ku, Mingjie Sun +8
Generative recommendation represents each item with a sequence of discrete Semantic IDs (SIDs) and predicts the sequence to retrieve the next item. Typical systems use multi-level…
RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems
Haoran Ling, Yuecheng Li, Zeyu Song +5
Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy changes. While LLM-based agents can…
CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
Lixiang Wang, Shaoyun Shi, Peng Wang +2
To balance effectiveness and efficiency in recommender systems, multi-stage pipelines employ lightweight two-tower models for large-scale candidate retrieval. However, their isolat…
CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
Lixiang Wang, Shaoyun Shi, Peng Wang +2
To balance effectiveness and efficiency in recommender systems, multi-stage pipelines commonly use lightweight two-tower models for large-scale candidate retrieval. However, the is…
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…
Jointly Optimizing Debiased CTR and Uplift for Coupons Marketing: A Unified Causal Framework
Siyun Yang, Shixiao Yang, Jian Wang +6
In online advertising, marketing interventions such as coupons introduce significant confounding bias into Click-Through Rate (CTR) prediction. Observed clicks reflect a mixture of…