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| # Embodied-R Model Weights | |
| This repository contains the RL-trained weights of the model introduced in the paper: | |
| **[Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning]**. | |
| For more details about the model and its implementation, please refer to the GitHub repository: | |
| [https://github.com/EmbodiedCity/Embodied-R.code](https://github.com/EmbodiedCity/Embodied-R.code). | |
| ## Citation | |
| If this work has contributed to your research, welcome to cite it: | |
| ``` | |
| @inproceedings{10.1145/3746027.3755703, | |
| author = {Zhao, Baining and Wang, Ziyou and Fang, Jianjie and Gao, Chen and Man, Fanhang and Cui, Jinqiang and Wang, Xin and Chen, Xinlei and Li, Yong and Zhu, Wenwu}, | |
| title = {Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning}, | |
| year = {2025}, | |
| isbn = {9798400720352}, | |
| publisher = {Association for Computing Machinery}, | |
| address = {New York, NY, USA}, | |
| url = {https://doi.org/10.1145/3746027.3755703}, | |
| doi = {10.1145/3746027.3755703}, | |
| booktitle = {Proceedings of the 33rd ACM International Conference on Multimedia}, | |
| pages = {11071–11080}, | |
| numpages = {10}, | |
| keywords = {embodied intelligence, reasoning, vision-language model}, | |
| location = {Dublin, Ireland}, | |
| series = {MM '25} | |
| } | |
| ``` | |
| --- | |
| license: mit | |
| --- | |