Meta Adaptive Ranking Model: Bending the Inference Scaling Curve to Serve LLM-Scale Models for Ads
中文摘要
Here are a few options for a 30-character Chinese summary, prioritizing clarity and impact: 1. **Meta LLM 广告 (Meta LLM Ads)** - (21 characters) - Simple and direct. 2. **Meta 广告模型 (Meta Ad Model)** - (20 characters) - Focuses on the core change. 3. **Meta 智能广告 (Meta Smart Ads)** - (20 characters) - Highlights the AI aspect. I recommend **Meta LLM 广告 (Meta LLM Ads)** as it’s the most concise and clearly communicates the key takeaway.
English Summary
Meta is scaling its ads recommendation systems to LLM-scale using an Adaptive Ranking Model to improve user experience and advertiser outcomes.
Meta continues to lead the industry in utilizing groundbreaking AI Recommendation Systems (RecSys) to deliver better experiences for people, and better results for advertisers. To reach the next frontier of performance, we are scaling Meta’s Ads Recommender runtime models to LLM-scale & complexity to further a deeper understanding of people’s interests and intent. This increase [...] Read More... The post Meta Adaptive Ranking Model: Bending the Inference Scaling Curve to Serve LLM-Scale Models for Ads appeared first on Engineering at Meta.