Author

Nathan Berrebbi

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#machine learning Preprint Sep 2026

LIGE-GR: A Smooth Leap from Ranking to Generative Recommendation in the LLM Era

Instead of rebuilding the entire recommendation stack from scratch, LIGE-GR generalizes the existing pointwise recommendation system into a listwise generation system, which allows mature recommender systems to benefit from listwise optimization while preserving compatibility with existing models, value functions, and...

Venkat Srinivas, Chen-Zhang He, Sam Woodmansee et al. · 0 citations

Jul 2026

SlimPer: Make Personalization Model Slim and Smart

SlimPer unifies sparse, dense, and sequence features within a single backbone and provides inherent interpretability through its attention mechanism, which yields measurable improvements in user engagement while streamlining the overall system and enabling effective modeling of 10k+ fine-grained user history events.

Siqi Wang, Xian-Jie Chen, Shaofen Deng et al. · arXiv.org · 1 citation