PWM-WROP

A 16B multimodal world model post-trained for object permanence in video generation and reasoning.

License and attribution

The fine-tuned weights in this repository are released under CC BY-NC 4.0 — attribution: Hokin Deng. Non-commercial use only. For commercial licensing contact hokinxqdeng@gmail.com.

Built on NVIDIA Cosmos. PWM-WROP is a derivative of the base model nvidia/Cosmos3-Nano (Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES), which NVIDIA distributes under the OpenMDW License Agreement 1.1. As that agreement requires, a copy is included here as LICENSE-OpenMDW-1.1.txt and NVIDIA's copyright notice is retained; its terms apply to the base-model portions of these weights, and the CC BY-NC 4.0 terms above apply to the fine-tuning as released.

Citation

Paper: Training Object Permanence in World Models — arXiv:2609.28654.

@misc{zhang2026trainingobjectpermanenceworld,
  title         = {Training Object Permanence in World Models},
  author        = {Haotian Zhang and Fengyuan Yu and Dezhi Luo and Haoran Sun and Zehong Zhao and Qingying Gao and Yihan Li and Siyuan An and Huayi Qin and Yilan Zhang and Zhengze Jiang and Pinyuan Feng and Renrui Zhang and Ziyu Guo and Letian Wang and Mengyue Yang and Kangfu Mei and Maijunxian Wang and Ran Ji and Vikash Kumar and Freda Shi and Chandra Sripada and Vincent C. Muller and Philip Torr and Alan Yuille and Nikolaus Kriegeskorte and Felix Juefei-Xu and Lvmin Zhang and Jieneng Chen and Yilun Du and Hokin Deng},
  year          = {2026},
  eprint        = {2609.28654},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2609.28654}
}