DesignLab: Designing Slides Through Iterative Detection and Correction
Designing high-quality presentation slides can be challenging for non-experts
due to the complexity involved in navigating various design choices. Numerous
automated tools can suggest layouts and color schemes, yet often lack the
ability to refine their own output, which is a key aspect in real-world
workflows. We propose DesignLab, which separates the design process into two
roles, the design reviewer, who identifies design-related issues, and the
design contributor who corrects them. This decomposition enables an iterative
loop where the reviewer continuously detects issues and the contributor
corrects them, allowing a draft to be further polished with each iteration,
reaching qualities that were unattainable. We fine-tune large language models
for these roles and simulate intermediate drafts by introducing controlled
perturbations, enabling the design reviewer learn design errors and the
contributor learn how to fix them. Our experiments show that DesignLab
outperforms existing design-generation methods, including a commercial tool, by
embracing the iterative nature of designing which can result in polished,
professional slides.
6881cb17df7c5aafaf37f0f1
Jooyeol Yun
claimed_verified
2025-07-24T09:13:01.588Z
6369f693bf21b20c5692937b
/avatars/e937dc8234b3e456149882bfce34841f.svg
Jooyeol Yun
user
YeolJoo
6881cb17df7c5aafaf37f0f2
Heng Wang
6881cb17df7c5aafaf37f0f3
Yotaro Shimose
6881cb17df7c5aafaf37f0f4
Jaegul Choo
6881cb17df7c5aafaf37f0f5
Shingo Takamatsu
DesignLab: Designing Slides Through Iterative Detection and Correction
Designing high-quality presentation slides can be challenging for non-experts
due to the complexity involved in navigating various design choices. Numerous
automated tools can suggest layouts and color schemes, yet often lack the
ability to refine their own output, which is a key aspect in real-world
workflows. We propose DesignLab, which separates the design process into two
roles, the design reviewer, who identifies design-related issues, and the
design contributor who corrects them. This decomposition enables an iterative
loop where the reviewer continuously detects issues and the contributor
corrects them, allowing a draft to be further polished with each iteration,
reaching qualities that were unattainable. We fine-tune large language models
for these roles and simulate intermediate drafts by introducing controlled
perturbations, enabling the design reviewer learn design errors and the
contributor learn how to fix them. Our experiments show that DesignLab
outperforms existing design-generation methods, including a commercial tool, by
embracing the iterative nature of designing which can result in polished,
professional slides.
DesignLab, an iterative design tool using fine-tuned language models, outperforms existing methods by refining design drafts through continuous error detection and correction.
large language models iterative design design reviewer design contributor controlled perturbations