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FeLiX is a new federated learning orchestration framework that optimizes time-to-target accuracy on live interaction streams by handling transient client availability, dynamic data heterogeneity, and outcome delays. It introduces streaming-aware availability tiers, fresh-utility selection, and delay-robust aggregation, reducing wall-clock time by up to 2.37x and communication bandwidth by 1.30x versus state-of-the-art baselines.
This paper proposes ARS, a memory-augmented agentic recommender system that treats recommendation as a partially observable problem with a hierarchical belief-state memory structure. It achieves state-of-the-art performance on four benchmarks with significant improvements over baselines.
Sephora partnered with OpenAI to deploy an AI shopping assistant on its website and in ChatGPT, increasing conversion rates by over 5%. It shared three key insights: guided experience, transparent recommendations, and continuous testing and learning.