Author

Yaodong Yang

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Jul 2026

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

Experiments across diverse upstream models show that PILA consistently improves ad effectiveness while preserving response quality, highlighting its promise as a practical solution for LLM-native advertising.

Zhaowei Zhang, Yuhan Fu, Yihang Zhang et al. · arXiv.org · 3 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