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Shengsheng Niu

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#reinforcement learning Book Open access Nov 2026

TUGB: A Two-stage Uncertainty-aware Generative Auto-Bidding Framework

Generative modeling, particularly Decision Transformers, shows promise in auto-bidding strategies. However, it struggles with limited exploration in static offline datasets, vulnerability to dynamic environmental shifts, and a reliance on heuristic return-to-go (RTG) specifications that may yield suboptimal performance...

Lu-Zhan Yuan, Chao Mi, Xia-Hao Shi et al. · 0 citations
Preprint Aug 2026

LangBP: Language-Guided Reasoning and Acting for Joint Bidding and Pricing

LangBP is proposed, a hierarchical framework for language-guided joint bidding and pricing that outperforms strong baselines, and online A/B tests further demonstrate business gains in real-world deployment on a large-scale e-commerce platform.

Jian-Qing Ding, Chuan Yang, Linghui Meng et al. · 0 citations

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