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Paper · arXiv 2409.16493

NoTeeline: Supporting Real-Time Notetaking from Keypoints with Large Language Models

Faria Huq, Abdus Samee, David Chuan-en Lin, Xiaodi Alice Tang, Jeffrey P. Bigham

10 upvotesSeptember 24, 2024arXiv 预印本
AI 摘要
interactive systemreal-timepersonalized noteskeypointsmicronotesfull-fledged notesphrase embeddingswriting stylewithin-subjects studyhigh-quality notesfactual correctnesssemantic consistencymental effortnotetaking timeTransformer-based detectorbaseline latencies

Abstract

Video has become a popular media form for information sharing and consumption. However, taking notes while watching a video requires significant time and effort. To address this, we propose a novel interactive system, NoTeeline, for taking real-time, personalized notes. NoTeeline lets users quickly jot down keypoints (micronotes), which are automatically expanded into full-fledged notes that capture the content of the user's micronotes and are consistent with the user's writing style. In a within-subjects study (N=12), we found that NoTeeline helps users create high-quality notes that capture the essence of their micronotes with a higher factual correctness (93.2%) while accurately reflecting their writing style. While using NoTeeline, participants experienced significantly reduced mental effort, captured satisfactory notes while writing 47% less text, and completed notetaking with 43.9% less time compared to a manual notetaking baseline.

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NoTeeline: Supporting Real-Time Notetaking from Keypoints with Large Language Models | TensorX