Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magnitudes under strict global constraints. This problem is complicated by high-frequency interactions, delayed feedback, and non-Markovian user dynamics such as fatigue, whi...
Gege Chen, Ning Luo, Hao Jiang et al.· Proceedings of the 32nd ACM...· 0 citations
Auto-bidding is central to computational advertising, where strategies must maximize advertisers'conversion value under economic constraints. It has evolved from rule-based controllers to reinforcement learning and generative methods such as Decision Transformer (DT). Yet these methods increasingly mismatch the prevail...
Ye-Wen Li, Peng Jiang, Yi-Tian Li et al.· 0 citations
Generative retrieval (GR) is a promising paradigm for industrial search advertising, yet its deployment is constrained by strict relevance and latency requirements. Existing systems cascade GR with an independent relevance model, decoupling the generative likelihood objective from query-ad relevance discrimination, whi...
Shujie Ji, Yawei Kong, Yili Zhao et al.· 0 citations
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