Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison

Query-driven recommendation with unknown items poses a challenge for users to understand why certain items are appropriate for their needs. Query-driven Contrastive Summarization (QCS) is a methodology designed to address this issue by leveraging languagebased item descriptions to clarify contrasts between them. However, existing state-of-theart contrastive summarization methods such as STRUM-LLM fall short of this goal. To overcome these limitations, we introduce Q-STRUM Debate, a novel extension of STRUM-LLM that employs debate-style prompting to generate focused and contrastive summarizations of item aspects relevant to a query. Leveraging modern large language models (LLMs) as powerful tools for generating debates, Q-STRUM Debate provides enhanced contrastive summaries. Experiments across three datasets demonstrate that Q-STRUM Debate yields significant performance improvements over existing methods on key contrastive summarization criteria, thus introducing a novel and performant debate prompting methodology for QCS. Global Culinary influences Chinese culinary influences are significant due to the city's large Thai-Chinese population. [33] The Italian population and culture have left a lasting impact on Melbourne's dining scene. [40] Unique Dining Experiences