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From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking
Meta introduces a multi-stage sequence model and dense tokenization with target-aware attention to scale sequence learning for ads ranking, achieving lifts in conversions and clicks.
From the source
Separating the sequence model into two complementary stages (upstream/offline user modeling and downstream/online ranking), enables model capacity to scale so that performance keeps improving without proportional increases in serving resources.
engineering.fb.com
Visit source ↗engineering.fb.com
- Announced
- 05 Aug 2026 19:20 UTC
- Detected
- 05 Aug 2026 21:32 UTC (+2h after)
