WoW-world-model commited on
Commit
1ba1ebc
·
verified ·
1 Parent(s): 8a75dda

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +67 -3
README.md CHANGED
@@ -1,3 +1,67 @@
1
- ---
2
- license: apache-2.0
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ language:
4
+ - en
5
+ library_name: transformers
6
+ tags:
7
+ - video-generation
8
+ - robotics
9
+ - embodied-ai
10
+ - physical-reasoning
11
+ - causal-reasoning
12
+ - inverse-dynamics
13
+ - wow
14
+ - arxiv:2509.22642
15
+ datasets:
16
+ - WoW-world-model/WoW-1-Benchmark-Samples
17
+ pipeline_tag: video-generation
18
+ base_model: wan
19
+ ---
20
+
21
+ # 🤖 WoW-1-Wan-14B-600k
22
+
23
+ **WoW-1-Wan-14B** is a 14-billion-parameter generative world model trained on **2 million real-world robot interaction trajectories**. It is designed to imagine, reason, and act in physically consistent environments, powered by SOPHIA-guided refinement and a co-trained **Inverse Dynamics Model**.
24
+
25
+ This model is part of the [WoW (World-Omniscient World Model)](https://github.com/wow-world-model/wow-world-model) project, introduced in the paper:
26
+
27
+ > **[WoW: Towards a World omniscient World model Through Embodied Interaction](https://arxiv.org/abs/2509.22642)**
28
+ > *Chi et al., 2025 – arXiv:2509.22642*
29
+
30
+ ## 🧠 Key Features
31
+
32
+ - **14B parameters** trained on **2M robot interaction samples**
33
+ - Learns **causal physical reasoning** from embodied action
34
+ - Generates physically consistent video and robotic action plans
35
+ - Uses **SOPHIA**, a vision-language critic, to refine outputs
36
+ - Paired with an **Inverse Dynamics Model** to complete imagination-to-action loop
37
+
38
+ ## 🧪 Training Data
39
+
40
+ - **600k** Real-world robot interaction trajectories
41
+ - Multimodal scenes including vision, action, and language
42
+
43
+ ## 🧩 Applications
44
+
45
+ - Zero-shot video generation in robotics
46
+ - Causal reasoning and physics simulation
47
+ - Long-horizon manipulation planning
48
+ - Forward and inverse control prediction
49
+
50
+ ## 📄 Citation
51
+
52
+ ```bibtex
53
+ @article{chi2025wow,
54
+ title={WoW: Towards a World omniscient World model Through Embodied Interaction},
55
+ author={Chi, Xiaowei and Jia, Peidong and Fan, Chun-Kai and Ju, Xiaozhu and Mi, Weishi and Qin, Zhiyuan and Zhang, Kevin and Tian, Wanxin and Ge, Kuangzhi and Li, Hao and others},
56
+ journal={arXiv preprint arXiv:2509.22642},
57
+ year={2025}
58
+ }
59
+ ```
60
+
61
+ ## 🔗 Resources
62
+
63
+ - 🧠 Project page: [wow-world-model.github.io](https://wow-world-model.github.io/)
64
+ - 💻 GitHub repo: [wow-world-model/wow-world-model](https://github.com/wow-world-model/wow-world-model)
65
+ - 📊 Dataset: [WoW-1 Benchmark Samples](https://huggingface.co/datasets/WoW-world-model/WoW-1-Benchmark-Samples)
66
+
67
+ ---