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

TL;DR

Polymind is a visual diagramming tool that uses multiple LLM-powered agents to support prewriting activities through parallel microtasks, enhancing collaboration and idea generation compared to traditional turn-taking LLM interactions.

Contribution

It introduces a novel parallel microtask workflow with customizable microtask management for collaborative prewriting using LLMs.

Findings

Users had greater customizability with Polymind than ChatGPT.

Polymind enabled quicker expansion of personalized ideas.

The system supports simultaneous microtask orchestration.

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.