Author

Yaodong Yang

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Jul 2026

PILA: Plug-and-Play Insertion for LLM-native Advertising

How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recently emerged as a critical problem. However, existing solutions entangle advertising with content generation inside a single model, which is incompatible with modern API...

Zhaowei Zhang, Yuhan Fu, Yihang Zhang et al. · arXiv.org · 2 citations

2025

STAR: Efficient Preference-based Reinforcement Learning via Dual Regularization

STAR is proposed, an efficient PbRL method that integrates preference margin regularization and policy regularization that improves feedback efficiency and facilitates more robust reward and value function learning.

Fengshuo Bai, Rui Zhao, Hongming Zhang et al. · Neural Information Processin... · 5 citations