Author

Ruiming Lu

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Preprint Sep 2026

GRP v0.1 Technical Report

Industrial recommendation systems rely on multi-stage cascades whose retrieval, ranking, and serving components are difficult to replace jointly. We present GRP, a generative recommendation framework that combines retrieval, ranking, and reward modeling in a single encoder-decoder model, and evaluate a progressive path...

Wen-Feng Zhuo, Vincent Xue, Charles Wei et al. · 0 citations

Jul 2026

LLM-Based Generative Retrieval for Snapchat Content Recommendation

The design and launch of SnapLGR, an LLM-based generative retrieval system for short-video recommendation at Snapchat shows that successful production SnapLGR requires joint design across representation learning, vocabulary grounding, and efficient training and serving.

Liam Collins, Jiwen Ren, Donald Loveland et al. · arXiv.org · 0 citations