Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866911174363185152 |
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| author | Liu, Yiren Shah, Viraj Suh, Sangho Siangliulue, Pao August, Tal Huang, Yun |
| author_facet | Liu, Yiren Shah, Viraj Suh, Sangho Siangliulue, Pao August, Tal Huang, Yun |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_20553 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation Liu, Yiren Shah, Viraj Suh, Sangho Siangliulue, Pao August, Tal Huang, Yun Human-Computer Interaction Artificial Intelligence Computation and Language 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. |
| title | Perspectra: Choosing Your Experts Enhances Critical Thinking in Multi-Agent Research Ideation |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2509.20553 |