SUMMPILOT: Bridging Efficiency and Customization for Interactive Summarization System

초록

This paper incorporates the efficiency of automatic summarization and addresses the challenge of generating personalized summaries tailored to individual users' interests and requirements. To tackle this challenge, we introduce SUMMPILOT, an interaction-based customizable summarization system. SUMMPILOT leverages a large language model to facilitate both automatic and interactive summarization. Users can engage with the system to understand document content and personalize summaries through interactive components such as semantic graphs, entity clustering, and explainable evaluation. Our demo and user studies demonstrate SUMMPILOT's adaptability and usefulness for customizable summarization. Copyright © 2025, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.