Google Proposes HA-MoE Architecture to Boost Cross-Content Ranking Fairness
_reachsumit · x · 2026-07-31
To address the ranking challenges of mixed heterogeneous content (e.g., articles, videos, UGC) in unified feeds, Google has proposed a Heterogeneity-Adaptive Mixture-of-Experts (HA-MoE) architecture.
By incorporating explicit heterogeneity context into gating networks and expert representations, this approach effectively improves cross-content-type ranking fairness without significantly increasing serving latency (under 0.5%). The method has been applied to the multi-task ranking model in Google Discover.
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