InstInfo: A Just-in-Time Literature Recommendation System for Presentations

The efficient discovery of academic literature is critical for research progress, yet many researchers have difficulties in finding literature. This work proposes InstInfo: a novel just-in-time literature recommendation system for presentations. InstInfo transcribes audio in real-time and recommends literature according to the ideas being discussed, thereby helping researchers ground presentations in academic literature while saving them the time of having to manually search. Informal usability studies show that InstInfo is easy to use and that researchers find value in the recommendations. InstInfo can be accessed at https://instinfo.com.

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Published
2025-07-13
DOI
https://doi.org/10.1145/3726302.3730146
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

InstInfo: A Just-in-Time Literature Recommendation System for Presentations

ChengXiang Zhai, R.M. Suresh, Kevin Ros
Topic Modeling
article

InstInfo: A Just-in-Time Literature Recommendation System for Presentations

ChengXiang Zhai, R.M. Suresh, Kevin Ros
article en

Abstract

The efficient discovery of academic literature is critical for research progress, yet many researchers have difficulties in finding literature. This work proposes InstInfo: a novel just-in-time literature recommendation system for presentations. InstInfo transcribes audio in real-time and recommends literature according to the ideas being discussed, thereby helping researchers ground presentations in academic literature while saving them the time of having to manually search. Informal usability studies show that InstInfo is easy to use and that researchers find value in the recommendations. InstInfo can be accessed at https://instinfo.com.

University of Illinois Urbana-Champaign (US)
National Science Foundation, Institute of Education Sciences, University of Illinois at Urbana-Champaign
Quality Education
Openalex Percentile: Top 92%
Topic Modeling
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