AIBullisharXiv – CS AI · Jun 97/10
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Beyond Item IDs: Scaling Short-Form-Video Recommendation via Semantic-Native Long Sequence Modeling
Researchers present a production-deployed recommendation system that scales short-form video suggestions to billion-user scale by replacing traditional Video IDs with semantic-native representations and introducing a compression transformer to reduce computational complexity. The framework achieves order-of-magnitude improvements in memory efficiency and enables longer user behavior sequences, delivering measurable gains in user engagement and content consumption metrics.