# Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States

Page: https://stenobird.com/podcast/daily-paper-cast-7079649/puffin-world-scaling-a-unified-multimodal-model-with-native-3d-world-states
Text version: https://stenobird.com/podcast/daily-paper-cast-7079649/puffin-world-scaling-a-unified-multimodal-model-with-native-3d-world-states.md
Podcast: [Daily Paper Cast](https://stenobird.com/podcast/daily-paper-cast-7079649)
Published: 2026-09-04T07:49:10+00:00
Episode link: https://share.transistor.fm/s/fa0f3c67
Audio file: https://media.transistor.fm/fa0f3c67/979a218f.mp3
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JSON: https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/puffin-world-scaling-a-unified-multimodal-model-with-native-3d-world-states
Duration seconds: 1323

## Resource

🤗 Upvotes: 29 | cs.CV Authors: Kang Liao, Yihang Luo, Xiao-Ming Wu, Linyi Jin, Size Wu, Chunyu Lin, Yao Zhao, Fei Wang, Wei Li, Chen Change Loy Title: Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States Arxiv: http://arxiv.org/abs/2609.04196v1 Abstract: We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial simulation, and 3D world generation and reconstruction without relying on external offline modules. To reliably construct and interact with 3D worlds, our framework jointly models three native world states: physics (gravity field and latitude), geometry (depth), and appearance (image), together with a unified Omni-Camera representation that supports diverse tasks and flexible motions. Beyond modeling these states, we introduce a strategy for propagating physical dynamics across future frames. By grounding absolute camera properties in the real world, Puffin-World enables physically consistent and visually stable world generation. We further couple appearance and geometry within a single generative process, jointly synthesizing each future view and reconstructing its underlying geometry. This unified paradigm enables interleaved closed-loop applications requiring synergy across multiple tasks, including mimic and self-calibrated world exploration. To scale Puffin-World to complex scenarios, we construct Puffin-16M, comprising 15 million vision-language-camera triplets and 1 million trajectories featuring various and challenging motions. To foster further research in this area, we released the code, models, and datasets.

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