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Recent advancements in Visual Language Models (VLMs) have made them crucial for visual question answering (VQA) in autonomous driving, enabling natural human-vehicle interactions.
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Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Deep vision-language fusion for autonomous driving planning
Y. Chen, L. Xie, and X. Wang · 2022
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Vision-language models for autonomous driving: A survey
X. Yang, W. Li, and L. Zhang · 2022
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Contextual question answering for autonomous driving
T. Chen, X. Zhang, and Y. Wang · 2023
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Language is not all you need: Aligning perception with language models
Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal, Shuming Ma, Tengchao Lv, Lei Cui, Owais Khan Mohammed, Barun Patra, et al · 2023
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Languagempc: Large language models as decision makers for autonomous driving
Hao Sha, Yao Mu, Yuxuan Jiang, Li Chen, Chenfeng Xu, Ping Luo, Shengbo Eben Li, Masayoshi Tomizuka, Wei Zhan, and Mingyu Ding · 2023
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Drivelm: Driving with graph visual question answering
Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Jens Beißwenger, Ping Luo, Andreas Geiger, and Hongyang Li · 2023
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On the road with gpt-4v (ision): Early explorations of visual-language model on autonomous driving
Multi-frame, lightweight & efficient vision-language models for question answering in autonomous driving, 2024
Akshay Gopalkrishnan, Ross Greer, and Mohan Trivedi · 2024
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Dialogue-based question answering for autonomous vehicles
Z. Li, H. Wang, and Y. Xu · 2024
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Vlm2scene: Self-supervised image-text-lidar learning with foundation models for autonomous driving scene understanding
Guibiao Liao, Jiankun Li, and Xiaoqing Ye · 2024
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Drivevlm: The convergence of autonomous driving and large vision-language models
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Drivegpt4: Interpretable end-to-end autonomous driving via large language model
Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kwan-Yee K Wong, Zhenguo Li, and Hengshuang Zhao · 2024
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Licheng Wen, Xuemeng Yang, Daocheng Fu, Xiaofeng Wang, Pinlong Cai, Xin Li, Tao Ma, Yingxuan Li, Linran Xu, Dengke Shang, et al · 2023
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Multimodal vision-language models for autonomous driving
Z. Zeng, L. Xie, and S. Wang · 2023
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Vision-language pretraining for autonomous driving decision making
J. Zhu, M. Li, and W. Hu · 2023
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Driving with llms: Fusing object-level vector modality for explainable autonomous driving
Long Chen, Oleg Sinavski, Jan Hünermann, Alice Karnsund, Andrew James Willmott, Danny Birch, Daniel Maund, and Jamie Shotton · 2024
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Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario
Tianwen Qian, Jingjing Chen, Linhai Zhuo, Yang Jiao, and Yu-Gang Jiang
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Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario, 2024b
Tianwen Qian, Jingjing Chen, Linhai Zhuo, Yang Jiao, and Yu-Gang Jiang
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al
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Generalized predictive model for autonomous driving
Jiazhi Yang, Shenyuan Gao, Yihang Qiu, Li Chen, Tianyu Li, Bo Dai, Kashyap Chitta, Penghao Wu, Jia Zeng, Ping Luo, et al · 2024
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End-to-end vision-language reasoning for autonomous driving
J. Zhang, L. Liu, and C. Wu · 2024
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Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving
Ming Nie, Renyuan Peng, Chunwei Wang, Xinyue Cai, Jianhua Han, Hang Xu, and Li Zhang · 2025
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