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

Yiren Liu, Viraj Shah, Sangho Suh, Pao Siangliulue, Tal August +1 more
9/24/2025
cs.HCcs.AIcs.CL

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Abstract

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.

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Cite this paper

@article{liu2025perspectra,
  title  = {Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation},
  author = {Yiren Liu and Viraj Shah and Sangho Suh and Pao Siangliulue and Tal August and Yun Huang},
  year   = {2025},
  eprint = {2509.20553},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.20553v1}
}

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