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Since the advent of Multimodal Large Language Models (MLLMs), they have made a significant impact across a wide range of real-world applications, particularly in Autonomous Driving (AD).
3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Kosecka · 2017
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst, 2018
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2019
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Pointpillars: Fast encoders for object detection from point clouds, 2019
Alex H. Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Accurate monocular 3d object detection via color-embedded 3d reconstruction for autonomous driving
Xinzhu Ma, Zhihui Wang, Haojie Li, Pengbo Zhang, Wanli Ouyang, and Xin Fan · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Scalability in perception for autonomous driving: Waymo open dataset, 2020
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Sheng Zhao, Shuyang Cheng, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
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End-to-end model-free reinforcement learning for urban driving using implicit affordances
Marin Toromanoff, Emilie Wirbel, and Fabien Moutarde · 2020
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A survey of autonomous driving: Common practices and emerging technologies
Ekim Yurtsever, Jacob Lambert, Alexander Carballo, and Kazuya Takeda · 2020
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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 · 2021
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End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2021
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Epro-pnp: Generalized end-to-end probabilistic perspective-n-points for monocular object pose estimation
Hansheng Chen, Pichao Wang, Fan Wang, Wei Tian, Lu Xiong, and Hao Li · 2022
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Pix2seq: A language modeling framework for object detection
Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, and Geoffrey Hinton · 2022
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Cramnet: Camera-radar fusion with ray-constrained cross-attention for robust 3d object detection, 2022
Jyh-Jing Hwang, Henrik Kretzschmar, Joshua Manela, Sean Rafferty, Nicholas Armstrong-Crews, Tiffany Chen, and Dragomir Anguelov · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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Hdmapnet: An online hd map construction and evaluation framework, 2022
Qi Li, Yue Wang, Yilun Wang, and Hang Zhao · 2022
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Wayformer: Motion forecasting via simple & efficient attention networks, 2022
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, and Benjamin Sapp · 2022
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Block-nerf: Scalable large scene neural view synthesis, 2022
Matthew Tancik, Vincent Casser, Xinchen Yan, Sabeek Pradhan, Ben Mildenhall, Pratul P. Srinivasan, Jonathan T. Barron, and Henrik Kretzschmar · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou · 2022
Cited alongside, same era.
Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
A survey of chain of thought reasoning: Advances, frontiers and future
Zheng Chu, Jingchang Chen, Qianglong Chen, Weijiang Yu, Tao He, Haotian Wang, Weihua Peng, Ming Liu, Bing Qin, and Ting Liu · 2023
Cited alongside, same era.
Trafficgen: Learning to generate diverse and realistic traffic scenarios
Lan Feng, Quanyi Li, Zhenghao Peng, Shuhan Tan, and Bolei Zhou · 2023
Cited alongside, same era.
Planning-oriented autonomous driving, 2023
Monoedge: Monocular 3d object detection using local perspectives
Minghan Zhu, Lingting Ge, Panqu Wang, and Huei Peng · 2023
Later among the works it cites.
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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End-to-end autonomous driving: Challenges and frontiers
Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, and Hongyang Li · 2024
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Emma: End-to-end multimodal model for autonomous driving
Jyh-Jing Hwang, Runsheng Xu, Hubert Lin, Wei-Chih Hung, Jingwei Ji, Kristy Choi, Di Huang, Tong He, Paul Covington, Benjamin Sapp, Yin Zhou, James Guo, Dragomir Anguelov, and Mingxing Tan · 2024
Closest in time.
Senna: Bridging large vision-language models and end-to-end autonomous driving, 2024
Bo Jiang, Shaoyu Chen, Bencheng Liao, Xingyu Zhang, Wei Yin, Qian Zhang, Chang Huang, Wenyu Liu, and Xinggang Wang · 2024
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Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, Lewei Lu, Xiaosong Jia, Qiang Liu, Jifeng Dai, Yu Qiao, and Hongyang Li · 2023
Cited alongside, same era.
Vad: Vectorized scene representation for efficient autonomous driving, 2023
Bo Jiang, Shaoyu Chen, Qing Xu, Bencheng Liao, Jiajie Chen, Helong Zhou, Qian Zhang, Wenyu Liu, Chang Huang, and Xinggang Wang · 2023
Cited alongside, same era.
Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
Cited alongside, same era.
Gpt-driver: Learning to drive with gpt, 2023
Jiageng Mao, Yuxi Qian, Junjie Ye, Hang Zhao, and Yue Wang · 2023
Cited alongside, same era.
Plum: Prompt learning using metaheuristic
Rui Pan, Shuo Xing, Shizhe Diao, Wenhe Sun, Xiang Liu, Kashun Shum, Renjie Pi, Jipeng Zhang, and Tong Zhang · 2023
Cited alongside, same era.
Code llama: Open foundation models for code
Baptiste Roziere, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 2023
Cited alongside, same era.
Motionlm: Multi-agent motion forecasting as language modeling, 2023
Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S. Refaat, Rami Al-Rfou, and Benjamin Sapp · 2023
Cited alongside, same era.
Drivelm: Driving with graph visual question answering
Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Ping Luo, Andreas Geiger, and Hongyang Li · 2023
Cited alongside, same era.
Closest in time.
Llava-next-interleave: Tackling multi-image, video, and 3d in large multimodal models
Feng Li, Renrui Zhang, Hao Zhang, Yuanhan Zhang, Bo Li, Wei Li, Zejun Ma, and Chunyuan Li · 2024
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Light the night: A multi-condition diffusion framework for unpaired low-light enhancement in autonomous driving
Jinlong Li, Baolu Li, Zhengzhong Tu, Xinyu Liu, Qing Guo, Felix Juefei-Xu, Runsheng Xu, and Hongkai Yu · 2024
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Comamba: Real-time cooperative perception unlocked with state space models
Jinlong Li, Xinyu Liu, Baolu Li, Runsheng Xu, Jiachen Li, Hongkai Yu, and Zhengzhong Tu · 2024
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Scenarionet: Open-source platform for large-scale traffic scenario simulation and modeling
Quanyi Li, Zhenghao Mark Peng, Lan Feng, Zhizheng Liu, Chenda Duan, Wenjie Mo, and Bolei Zhou · 2024
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Is ego status all you need for open-loop end-to-end autonomous driving?, 2024
Zhiqi Li, Zhiding Yu, Shiyi Lan, Jiahan Li, Jan Kautz, Tong Lu, and Jose M. Alvarez · 2024
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
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Llama 3.2: Revolutionizing edge ai and vision with open, customizable models
Meta · 2024
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Hello gpt-4o
OpenAI · 2024
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Monodiff: Monocular 3d object detection and pose estimation with diffusion models
Yasiru Ranasinghe, Deepti Hegde, and Vishal M. Patel · 2024
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Lmdrive: Closed-loop end-to-end driving with large language models
Hao Shao, Yuxuan Hu, Letian Wang, Guanglu Song, Steven L Waslander, Yu Liu, and Hongsheng Li · 2024
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Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying, 2024
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2024
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Qwen2.5: A party of foundation models, September 2024
Qwen Team · 2024
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Drivevlm: The convergence of autonomous driving and large vision-language models
Xiaoyu Tian, Junru Gu, Bailin Li, Yicheng Liu, Chenxu Hu, Yang Wang, Kun Zhan, Peng Jia, Xianpeng Lang, and Hang Zhao · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Yang Fan, Kai Dang, Mengfei Du, Xuancheng Ren, Rui Men, Dayiheng Liu, Chang Zhou, Jingren Zhou, and Junyang Lin · 2024
Closest in time.
AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
Shuo Xing, Hongyuan Hua, Xiangbo Gao, Shenzhe Zhu, Renjie Li, Kexin Tian, Xiaopeng Li, Heng Huang, Tianbao Yang, Zhangyang Wang, Yang Zhou, Huaxiu Yao, and Zhengzhong Tu · 2024
Closest in time.
Jianhao Yuan, Shuyang Sun, Daniel Omeiza, Bo Zhao, Paul Newman, Lars Kunze, and Matthew Gadd · 2024
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Position: Prospective of autonomous driving - multimodal llms, world models, embodied intelligence, ai alignment, and mamba
LLVM-AD Workshop Committee · 2025
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