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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
Preprint Aug 2026

Decoupling Generation and Selection for Budget-Constrained Faithful Summarization

Abstractive summarization models remain vulnerable to factual inconsistency, redundancy, and weak length control. We propose a modular generation-and-selection framework for sentence-budget-constrained summarization. A pretrained generator produces multiple candidate summaries, which are decomposed into sentence-level...

Zeyu Wang, Guanghua Wang, Mengyu Xu · 0 citations

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