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Ming-Yan Gao

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#machine learning Preprint Oct 2026

Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective

Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions, faces critical stability challenges. Rapid distribution shifts in user data and increasing model complexity frequently trigger a divergence cascade, typically initiating...

Yue-Ning Li, Ze-Yu Wang, Zhen Zhang et al. · 0 citations
#artificial intelligence Book Open access Jul 2026

RecEvolve: A Knowledge-Driven Autonomous Agent System for Recommender Systems

These findings prove that an autonomous pipeline can dramatically accelerate the pace of machine learning research and stress-test the rigorousness of underlying experimental infrastructure, while also exposing novel challenges such as reward hacking and redundant exploration of failed hypotheses.

W. Pan, He Ma, Shu-Hao Ye et al. · 1 citation

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