# CreativeFlow: A One-to-Many Analogical Relation Transfer Method for 3D Asset Generation

arXiv: https://arxiv.org/abs/2610.05167 · HTML: https://mlsanity.com/paper/2610.05167/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 10 references that are in the map.
- First posted on arXiv 4 Oct 2026.

## Builds on (most cited first, 1 of 1)

- [Beyond Input-Output: Rethinking Creativity through Design-by-Analogy in Human-AI Collaboration](https://mlsanity.com/paper/2602.09423/) (2026)

## Abstract (arXiv)

Inspired by cognitive science, we present CREATIVEFLOW, an analogical generation framework that explicitly models analogical divergent thinking to mitigate creative homogenization in text-to-3D pipelines. Our method derives a series of meaningful yet relationally similar source-target asset pairs, each featuring distinct geometric configurations. Expert evaluations demonstrate that our framework substantially enhances creative novelty and visual fascination. This workflow and its resulting assets establish a foundational dataset and benchmark for future relation-aware 3D model training.