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Evaluated on recommendation models, Auto-RecSys significantly reduces the human time required per experiment cycle and improves execution reliability as its playbooks mature.
Forget quadratic complexity: ULTRA-HSTU achieves 21x faster inference and 4-8% better engagement in large-scale recommendation by co-designing input sequences, sparse attention, and model topology.
