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.
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