Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation
Early-stage interdisciplinary research ideation is often challenged by limited expert access, uncertainty about what to ask, and the cognitive burden of synthesizing unfamiliar domain perspectives. This paper presents Perspectra, a forum-style multi-agent system that structures and visualizes deliberation among LLM-simulated domain experts to support exploration and refinement of emerging research ideas, while encouraging critical thinking and reflections. The interface design combines 1) a threaded canvas for parallel topic exploration with visualization of agent discourse dynamics informed by argumentation theory to aid sensemaking; and 2) feature that enables users to invite multiple self-chosen agents into an ongoing discussion. We conducted a user study with 18 participants, comparing Perspectra against a vanilla chat baseline given a task for the user to develop a short research proposal. Our findings show that Perspectra’s design elicits significantly more higher-order critical thinking behaviors during interactions with agents when compared to a traditional chat interface. We also observed more interdisciplinary user replies via forum-styled design, and more frequent and structured proposal revisions (rather than unstructured note-taking). Based on our findings, we further contribute interaction design implications of using multi-agent deliberation for complex ideation and knowledge search, combining flexibility with structured exploration to support user sensemaking and critical thinking.
Authors
- Pao Siangliulue (ORCID: https://orcid.org/0009-0006-8042-885X)
- Tal August (ORCID: https://orcid.org/0000-0001-6726-4009)
- Sangho Suh (ORCID: https://orcid.org/0000-0003-4617-5116)
- Yiren Liu (ORCID: https://orcid.org/0000-0003-1507-0303)
Institutions
- University of Illinois Urbana-Champaign (US)
- Allen Institute (US)
Publication Details
- Published
- 2026-04-13
- DOI
- https://doi.org/10.1145/3772318.3791560
- Primary Topic
- Complex Systems and Decision Making
- Type
- article
- Field-Weighted Citation Impact
- 0.00