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Wukong (Meta)

Definition

Wukong is the Meta Ads internal recommendation / ranking model architecture published in 2024 at arXiv:2403.02545. It is the foundational design underpinning Meta's trajectory toward LLM-scale ads ranking, and the architectural basis for Wukong Turbo, the runtime evolution deployed inside Meta Adaptive Ranking Model (Source: sources/2026-03-31-meta-adaptive-ranking-model-bending-the-inference-scaling-curve).

Architectural primitives (summary from Adaptive Ranking Model

post)

  • Stackable factorisation machines — layered FM blocks for cross-feature interactions, allowing depth to be stacked for richer modelling.
  • Sequence learning — over user behaviour histories, the input that the request- oriented sequence scaling optimisation later amortises across ad candidates.
  • Cross-layer attention — attention mechanisms spanning architectural depth, not just within individual blocks.

These three primitives are named in the 2026-03-31 Adaptive Ranking Model post; the full architecture is described in the Wukong paper itself (not ingested into this wiki).

Relationship to Wukong Turbo + Adaptive Ranking Model

Wukong is the model architecture. Wukong Turbo is the optimised serving-side runtime that layers no-bias numerical stability, FSDP→DDP parameter delegation, and sparsity-based linear simplification on top — refinements that allow Wukong's depth + parameter count to scale without blowing the sub-second latency budget.

Caveats

  • Stub — this page summarises only what the 2026-03-31 Meta Adaptive Ranking Model post names about Wukong. The full architecture is described in arXiv:2403.02545, which is not ingested into this wiki.
  • Candidate for deeper future ingestion if further Wukong or Meta ads-ranking content surfaces.

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