AI RESEARCH
FlowTime: Towards Continuous Generative Watch Time Prediction via Flow-based Personalized Priors
arXiv CS.AI
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ArXi:2606.01352v1 Announce Type: new Watch time has emerged as a pivotal metric for optimizing deep user engagement in short-video recommender systems. However, current methods of watch time prediction (WTP) suffer from inherent paradigm-specific limitations. Direct Regression faces mean-collapse due to unimodal Gaussian assumptions, while Ordinal Regression is hampered by quantization errors from rigid discretization. Similarly, Discrete Generative Regression struggles with high inference latency and heuristic vocabulary design.