SUMMPILOT: Bridging Efficiency and Customization for Interactive Summarization System
This addresses the problem of customizable summarization for users needing personalized document insights, though it appears incremental as it builds on existing summarization and interaction techniques.
The paper tackles the challenge of generating personalized summaries tailored to individual users' interests by introducing SummPilot, an interaction-based customizable summarization system that leverages a large language model, with user studies demonstrating its adaptability and usefulness.
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.