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From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
Fb.com·August 5, 2026·1 min read
AI Summary
Meta's recommendation platforms process billions of user interactions daily, leveraging temporal signals to enhance ads ranking. A new multi-stage architecture aims to improve how these systems understand user preferences and intent.
From the source
Every day, Meta’s recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for ads recommendations, …
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