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Decision-Oriented Recommendation Reranking: An Empirical Study of Jev

This study explores Jev, a decision-oriented model described as a 'System One Model,' for personalized recommendation reranking, comparing its performance with recommendation-specific models and Qwen rerankers across multiple Amazon Reviews domains and candidate-set sizes. Results show Jev maintains strong recommendation effectiveness with more gradual latency growth compared to pointwise Qwen rerankers, though its serving latency remains higher than recommendation-specific models.

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PublishedSeptember 30, 2026Hanjia Lyu, Yinglong Xia
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WHY IT MAY MATTER

Jev offers a balanced approach between recommendation quality and serving efficiency, making it suitable for scenarios where structured decision-making is crucial despite higher latency compared to specialized models.

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