Nitin Yadav

Learning to Summarize for Search Relevance with Reinforcement Learning

ReLSum is a reinforcement learning framework that generates concise, relevance-optimized product summaries for search ranking by using downstream relevance scores as reward signals and enables summaries to be generated and cached offline, ensuring no additional inference latency at serving time.