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arXiv AI By Victor Zhang, Yiping Yuan, Florian Raudies, Bosun Adeoti, Brian Y. C. Leung, Sanjay Surendranath Girija, Naijing Zhang

Learned Cross-Task Relationships in Multi-Task Models

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The paper introduces a framework that learns cross‑task relationships in multi‑task models by approximating the joint distribution of task labels through targeted pairwise relationships. This method improves performance via transfer learning and enhances information extraction without the intractable complexity of modeling the full joint space. The authors demonstrate its effectiveness in YouTube’s production recommendation systems, showing gains in accuracy and user satisfaction across Notifications, Homepage, and Watch Next surfaces, and provide a workflow template for broader implementation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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