collaborators

5 papers

cs.CV2026

Dream-Cubed: Controllable Generative Modeling in Minecraft by Training on Billions of Cubes

Tim Merino, Sam Earle, Ryunosuke Iwai +2

We introduce Dream-Cubed, a large-scale dataset of Minecraft worlds at voxel resolution, and a family of models using cubes as powerful compositional units for efficient generation…

cs.AI2025

A Markovian Framing of WaveFunctionCollapse for Procedurally Generating Aesthetically Complex Environments

Franklin Yiu, Mohan Lu, Nina Li +5

Procedural content generation often requires satisfying both designer-specified objectives and adjacency constraints implicitly imposed by the underlying tile set. To address the c…

cs.AI2025

All Stories Are One Story: Emotional Arc Guided Procedural Game Level Generation

Yunge Wen, Chenliang Huang, Hangyu Zhou +5

The emotional arc is a universal narrative structure underlying stories across cultures and media -- an idea central to structuralist narratology, often encapsulated in the phrase…

cs.HC2025

God's Innovation Project -- Empowering The Player With Generative AI

Ritvik Nair, Timothy Merino, Julian Togelius

In this paper, we present God's Innovation Project (GIP), a god game where players collect words to dynamically terraform the landscape using generative AI. A god game is a genre w…

cs.AI2025

Moonshine: Distilling Game Content Generators into Steerable Generative Models

Yuhe Nie, Michael Middleton, Tim Merino +4

Procedural Content Generation via Machine Learning (PCGML) has enhanced game content creation, yet challenges in controllability and limited training data persist. This study addre…