ARC
Designing for strategic exploration and responsible AI in systematic literature reviews.

Systematic literature reviews are fundamental to scientific progress, but the work is spread across a fragmented tool ecosystem that imposes a high cognitive load and suppresses the iterative, exploratory side of scholarship. An exploratory design study with 20 experienced researchers surfaced three friction points: refining queries across multiple databases, the scale and pace of modern publishing, and the tension between automation and scholarly agency.
ARC is a design probe built from those findings. It brings multi-database search, a transparent record of how a query evolved, and verifiable AI-assisted screening into a single environment. In a comparative study with 8 researchers, that integration moved effort away from administrative overhead and toward strategic exploration, using external representations and visible AI reasoning to keep expert judgement in the loop.
People
CORE Lab
- Harry (Runlong) YePh.D. Student, Computer Science — University of Toronto
- Naaz SibiaPh.D. Candidate, Computer Science — University of Toronto
- Angela Zavaleta BernuyCo-Director, CORE Lab; Assistant Professor, Computing and Software — McMaster University
- Michael LiutCo-Director, CORE Lab; Associate Professor, Teaching Stream — University of Toronto Mississauga
Collaborators
Papers
- Runlong Ye, Naaz Sibia, Angela Zavaleta Bernuy, Tingting Zhu, Carolina Nobre, Viktoria Pammer-Schindler, Michael Liut."From Toil to Thought: Designing for Strategic Exploration and Responsible AI in Systematic Literature Reviews" Proceedings of the 31st International Conference on Intelligent User Interfaces. (2026).[doi][]






