Ningren (Peter) Han

AI Researcher @GoogleDeepMind | PhD @MIT EECS, BEng @NUSingapore EE

[Yueqi Wang @yueqiw]

It's been a lot of fun working on this research, enabling extremely efficient constrained decoding for YouTube's LLM-based recommender system (https://t.co/dAqqLfuLxx).

It's also a great add-on to our PLUM generative retrieval framework (https://t.co/bgy193ayWe).

[Sumit @_reachsumit]

LLM-Powered Nuanced Video Attribute Annotation for Enhanced Recommendations

@BoyuanLong et al. at Google use LLMs as annotators to achieve nuanced content understanding at scale for video recommendations.

📝https://t.co/kzjPCyXtHr

[Sumit @_reachsumit]

PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations

Google adapts pre-trained LLMs for large-scale recommendation through Semantic ID tokenization, continued pre-training, and generative retrieval.

📝https://t.co/GPJzPWjYHL

[Ningren (Peter) Han @peterhannh]

@_reachsumit @BoyuanLong Great work! @BoyuanLong