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cs.IR2026
Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective
Yuening Li, Zeyu Wang, Zhen Zhang +8
Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions, faces critical stability chal…
cs.IR2026
RecEvolve: A Knowledge-Driven Autonomous Agent System for Recommender Systems
Weidi Pan, He Ma, Shuhao Ye +6
The rise of agentic AI has catalyzed a shift toward self-iterating systems, opening new frontiers for the autonomous optimization of production recommender models. This paper prese…