Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation

要旨

Recent advances in multi-agent systems (MAS) enable tools for information search and ideation by assigning personas to agents. However, how users can effectively control, steer, and critically evaluate collaboration among multiple domain-expert agents remains underexplored. We present Perspectra, an interactive MAS that visualizes and structures deliberation among LLM agents via a forum-style interface, supporting @-mention to invite targeted agents, threading for parallel exploration, with a real-time mind map for visualizing arguments and rationales. In a within-subjects study with 18 participants, we compared Perspectra to a group-chat baseline as they developed research proposals. Our findings show that Perspectra significantly increased the frequency and depth of critical-thinking behaviors, elicited more interdisciplinary replies, and led to more frequent proposal revisions than the group chat condition. We discuss implications for designing multi-agent tools that scaffold critical thinking by supporting user control over multi-agent adversarial discourse.

受賞
Honorable Mention
著者
Yiren Liu
University of Illinois Urbana-Champaign, Champaign, Illinois, United States
Viraj Nischal Shah
University of Illinois Urbana Champaign, New York City, New York, United States
Sangho Suh
University of Toronto, Toronto, Ontario, Canada
Pao Siangliulue
Allen Institute for AI, Seattle, Washington, United States
Tal August
University of Illinois Urbana-Champaign , Urbana, Illinois, United States
Yun Huang
University of Illinois at Urbana-Champaign, Champaign, Illinois, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Multi-Agent Reasoning Systems for Sensemaking and Planning

P1 - Room 134
7 件の発表
2026-04-17 18:00:00
2026-04-17 19:30:00