2 papers
cs.IR2026
GenRec: An LLM-Backed Recommendation Ranker at Netflix
Ying Li, Shradha Sehgal, Arjun Rao +3
Large language models (LLMs) are reshaping recommender systems by enabling richer modeling of users, content, and context directly in natural language. At Netflix, we are exploring…
cs.IR2026
Multimedia Asset Personalization via Multimodal Embeddings at Netflix
Emma Yanyang Kong, Aditya Deshpande, Bowei Yan +5
Personalized promotional assets, namely artwork images and video preview clips, are critical to content discovery on Netflix. Traditional models for asset selection rely on ID-base…