<ul><li>Lusifer is an LLM-based simulation environment designed to generate dynamic, realistic user feedback for RL-based recommender training.</li><li>Lusifer updates user profiles at each interaction step using Large Language Models (LLMs) and provides transparent explanations of how and why preferences evolve.</li><li>By processing textual metadata, Lusifer creates context-aware user states and simulates feedback on new items, reducing reliance on extensive historical data and facilitating adaptation to out of distribution cases.</li><li>Lusifer excels in capturing dynamic user responses and yielding explainable results, making it a scalable and ethically sound alternative to live user experiments in RL-based recommender systems.</li></ul>

Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems

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