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Shawn Andrews

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Book Open access Sep 2026

Uncertainty-Aware Reward Modeling: A Large-Scale Case Study in Video Recommendation

Historically, recommendation systems have focused on maximizing precision by treating user preference as a static, predictable target. However, this approach ignores both the inherent randomness of human behavior and the model’s own varying levels of confidence. To compensate, many industrial systems rely on "reserved...

Nitu Sharaff, Brian Y. C. Leung, Shawn Andrews et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Lightweight Ranking Heads: Accelerating Multi-Task Experimentation in Production Recommender Systems

Modern production-scale recommender systems rely on complex, multi-task ranking models. Introducing new prediction tasks into these massive systems often causes bottlenecks - it risks negative task conflicts with existing tasks, and can lead to long development and experimentation cycles due to the expensive retraining...

Sanjay Surendranath Girija, Aniruddh Nath, Li Wei et al. · 0 citations

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