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.
Authors
- ChengXiang Zhai (ORCID: https://orcid.org/0000-0002-6434-3702)
- R.M. Suresh
- Kevin Ros (ORCID: https://orcid.org/0009-0007-0961-2694)
Institutions
- University of Illinois Urbana-Champaign (US)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3730146
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Institute of Education Sciences
- University of Illinois at Urbana-Champaign