OpenOneRec Technical Report: Advancing Recommender Systems

Research Paper#Recommender Systems, AI, Machine Learning🔬 Research|Analyzed: Jan 3, 2026 08:43
Published: Dec 31, 2025 10:15
1 min read
ArXiv

Analysis

This paper introduces RecIF-Bench, a new benchmark for evaluating recommender systems, along with a large dataset and open-sourced training pipeline. It also presents the OneRec-Foundation models, which achieve state-of-the-art results. The work addresses the limitations of current recommendation systems by integrating world knowledge and reasoning capabilities, moving towards more intelligent systems.
Reference / Citation
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"OneRec Foundation (1.7B and 8B), a family of models establishing new state-of-the-art (SOTA) results across all tasks in RecIF-Bench."
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ArXivDec 31, 2025 10:15
* Cited for critical analysis under Article 32.