2 papers
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…
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…