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GRACE system accelerates real-time ad retrieval with generative recommenders

By PulseAugur Editorial · [2 sources] ·

A new research paper introduces GRACE, a system designed to accelerate generative recommenders for real-time ad retrieval. GRACE addresses challenges in eligibility and compute by implementing Generative Target Matching (GTM) for improved ad targeting and optimizing encoder-decoder Transformers for reduced latency and cost. The system achieves significant performance gains on NVIDIA GH200 hardware, reducing cross-attention latency by up to 68 times and overall decoder latency by 11.1 times. AI

IMPACT This research could lead to more efficient and cost-effective real-time ad generation systems.

RANK_REASON The cluster contains a research paper detailing a new system for generative recommenders.

Read on arXiv cs.IR (Information Retrieval) →

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

GRACE system accelerates real-time ad retrieval with generative recommenders

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The cluster contains a research paper detailing a new system for generative recommenders.
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COVERAGE [2]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Gaoxiang Liu ·

    GRACE: Generative Recommender Acceleration Engine for Real-Time Ads Retrieval

    Productionizing generative recommenders for high-volume, real-time ads retrieval creates two serving challenges: eligibility, ensuring that each generated ad is eligible for the request under the advertiser's audience targeting rules, and compute, which requires meeting strict la…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Gaoxiang Liu ·

    GRACE: Generative Recommender Acceleration Engine for Real-Time Ads Retrieval

    Productionizing generative recommenders for high-volume, real-time ads retrieval creates two serving challenges: eligibility, ensuring that each generated ad is eligible for the request under the advertiser's audience targeting rules, and compute, which requires meeting strict la…

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