Polymind: Parallel Visual Diagramming with Large Language Models to Support Prewriting Through Microtasks

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables users to orchestrate multiple microtasks simultaneously. Users can configure and delegate customised microtasks, and manage their microtasks by specifying task requirements and toggling visibility and initiative. Our evaluation revealed that, compared to ChatGPT, users had more customizability over collaboration with Polymind, and were thus able to quickly expand personalised writing ideas during prewriting.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757497
Primary Topic
Interactive and Immersive Displays
Type
article
Field-Weighted Citation Impact
0.00
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article

Polymind: Parallel Visual Diagramming with Large Language Models to Support Prewriting Through Microtasks

Qian Wan, Zhicong Lu, Jiannan Li, Huanchen Wang
Proceedings of the ACM on Human-Computer Interaction
Interactive and Immersive Displays
article

Polymind: Parallel Visual Diagramming with Large Language Models to Support Prewriting Through Microtasks

Qian Wan, Zhicong Lu, Jiannan Li, Huanchen Wang
article en

Abstract

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables users to orchestrate multiple microtasks simultaneously. Users can configure and delegate customised microtasks, and manage their microtasks by specifying task requirements and toggling visibility and initiative. Our evaluation revealed that, compared to ChatGPT, users had more customizability over collaboration with Polymind, and were thus able to quickly expand personalised writing ideas during prewriting.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
George Mason University (US), City University of Hong Kong (HK), Southern University of Science and Technology (CN), Singapore Management University (SG)
Openalex Percentile: Top 71%
Interactive and Immersive Displays
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Polymind: Parallel Visual Diagramming with Large Language Models to Support Prewriting Through Microtasks — Qian Wan, Zhicong Lu, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS