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@@ -39,7 +39,8 @@ In this work, we use fine-tuned VLMs to provide feedback for reinforcement learn
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  - **Purpose:** To provide a holistic spatial understanding of the driving environment, allowing the VLM to act as an expert.
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  If you use these VLMs in your research, please cite our paper:
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- @misc{qu2026foundrlfoundationmodelenhancedreinforcement,
 
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  title={Found-RL: foundation model-enhanced reinforcement learning for autonomous driving},
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  author={Yansong Qu and Zihao Sheng and Zilin Huang and Jiancong Chen and Yuhao Luo and Tianyi Wang and Yiheng Feng and Samuel Labi and Sikai Chen},
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  year={2026},
 
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  - **Purpose:** To provide a holistic spatial understanding of the driving environment, allowing the VLM to act as an expert.
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  If you use these VLMs in your research, please cite our paper:
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+ ```bibtex
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+ @misc{qu2026foundrl,
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  title={Found-RL: foundation model-enhanced reinforcement learning for autonomous driving},
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  author={Yansong Qu and Zihao Sheng and Zilin Huang and Jiancong Chen and Yuhao Luo and Tianyi Wang and Yiheng Feng and Samuel Labi and Sikai Chen},
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  year={2026},