Author

Chang-Fa Wu

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Jul 2026

LoopMemGR: From Behavior Logs to Evolving Memory for Generative Recommendation

LoopMemGR is proposed, a closed-loop recommendation experience memory framework for generative recommendation that maintains a recommendation experience log that records past recommendation--feedback trajectories and extracts request-relevant evidence through three complementary views.

Hui Qian, Chang-Fa Wu, Chang Liu et al. · arXiv.org · 0 citations

Preprint Jul 2026

Prompt Generation Technical Report

Generative retrieval has become an increasingly adopted paradigm for industrial search, recommendation, and advertising systems, delivering significant online gains. Most existing work combines user behavior sequences with large language models (LLMs) to model user preferences. In practice, feature engineering remains...

Dan Ou, Gui Ling, Haokai Wan et al. · 0 citations