In this episode, we delve into the paper "TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest" . This research introduces TransAct, a novel Transformer-based model designed to enhance Pinterest's recommendation system by capturing users' short-term preferences through their real-time activities.​Research Paper Link - arxiv.org+4arxiv.org+4export.arxiv.org+4🔹 What’s Inside?Hybrid Ranking Approach – Combines real-time user behavior with long-term embeddings for better recommendations.Production Deployment – Powers multiple Pinterest surfaces like Homefeed, Search, and Notifications.Proven Impact – A/B tests show improved recommendation quality and engagement.Tune in to learn how TransAct balances real-time responsiveness with efficiency in large-scale AI-driven personalization. 🚀

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