A distilled LLM generates real-time, natural-language user interest personas—combining summarized interests with novel exploration topics—and this system produced small but significant viewer-value gains in a billion-user A/B test.
Chi, Lichan Hong, Ningren Han, and Haokai Lu
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.IR 2years
2026 2representative citing papers
Advocates prioritizing explicit contextual feedback in LLM-based recommender systems to improve user preference alignment and explainability.
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LLM-Based User Personas for Recommendations at Scale
A distilled LLM generates real-time, natural-language user interest personas—combining summarized interests with novel exploration topics—and this system produced small but significant viewer-value gains in a billion-user A/B test.
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Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback
Advocates prioritizing explicit contextual feedback in LLM-based recommender systems to improve user preference alignment and explainability.