NoteBar: An AI-Assisted Note-Taking System for Personal Knowledge Management
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Abstract (arXiv)
Note-taking is a critical practice for capturing, organizing, and reflecting on information in both academic and professional settings. The recent success of large language models has accelerated the development of AI-assisted tools, yet existing solutions often struggle with efficiency. We present NoteBar, an AI-assisted note-taking tool that leverages persona information and efficient language models to automatically organize notes into multiple categories and better support user workflows. To support research and evaluation in this space, we further introduce a novel persona-conditioned dataset of 3,173 notes and 8,494 annotated concepts across 16 MBTI personas, offering both diversity and semantic richness for downstream tasks. Finally, we demonstrate that NoteBar can be deployed in a practical and cost-effective manner, enabling interactive use without reliance on heavy infrastructure. Together, NoteBar and its accompanying dataset provide a scalable and extensible foundation for advancing AI-assisted personal knowledge management.
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References · 11
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
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- 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 417
- 2023Faithful Persona-based Conversational Dataset Generation with Large Language Modelscited by 47
- 2024GazeNoter: Co-Piloted AR Note-Taking via Gaze Selection of LLM Suggestions to Match Users' Intentionscited by 4
- 2024NoTeeline: Supporting Real-Time, Personalized Notetaking with LLM-Enhanced Micronotescited by 1
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