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Yandex Music's Sona recommender unifies generation and ranking, boosting engagement · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced Sona, a novel single-model generative recommender system designed for Yandex Music. In an online A/B test, Sona successfully replaced a complex, multi-stage production cascade, which included over 15 candidate generators and multiple ranking models. The new system unified candidate generation and ranking around a shared user representation, leading to significant improvements in key engagement metrics, including a 4.53% increase in Active Users and a 6.30% rise in Total Listening Time. AI

IMPACT This research demonstrates the potential for single, jointly trained models to replace complex multi-stage recommendation systems, potentially simplifying infrastructure and improving performance in large-scale applications.

RANK_REASON Publication of a technical report detailing a new model and its performance in an A/B test.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Yandex Music's Sona recommender unifies generation and ranking, boosting engagement · 2 sources tracked

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Publication of a technical report detailing a new model and its performance in an A/B test.
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2 independent sources
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model release, product, infra
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High
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46 days old
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COVERAGE [2]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Vladislav Tytskiy ·

    Sona Technical Report

    We introduce Sona, a single-model generative recommender for Yandex Music. In an online A/B test, Sona replaced the entire production cascade, comprising more than 15 candidate generators followed by pre-ranking and ranking models that consume hundreds of features, including sign…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Vladislav Tytskiy ·

    Sona Technical Report

    We introduce Sona, a single-model generative recommender for Yandex Music. In an online A/B test, Sona replaced the entire production cascade, comprising more than 15 candidate generators followed by pre-ranking and ranking models that consume hundreds of features, including sign…

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