ZoRRO: A Zero-Weight Personalized Recommender System for Scalable News Recommendation

Jul 14, 2026

ZoRRO is a training-free, zero-weight framework for personalized news recommendation designed for scalable real-world deployment. According to offline evaluations, ZoRRO outperforms strong neural baselines in ranking tasks and, in online A/B testing, achieves click-through rates nearly on par with a state-of-the-art deep learning model, while operating over 600 times faster. The study also finds that models with similar click-through rates can produce different recommendation distributions, affecting the flow of news content.

Why it matters: ZoRRO demonstrates a highly efficient and practical alternative to deep learning models for large-scale news recommendation, emphasizing the need for evaluation metrics beyond accuracy.

Full story at: arXiv Information Retrieval ↗