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A longstanding challenge for self-driving development is simulating dynamic driving scenarios seeded from recorded driving logs.
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 · 1903
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Fastdraw: Addressing the long tail of lane detection by adapting a sequential prediction network
Jonah Philion · 1905
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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 · 1910
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Stochastic sampling in computer graphics
Robert L. Cook · 1986
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2001
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K-means++: The advantages of careful seeding
David Arthur and Sergei Vassilvitskii · 2007
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Efficient reductions for imitation learning
Stephane Ross and Drew Bagnell · 2010
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Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba · 2016
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Wavenet: A generative model for raw audio
Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W. Senior, and Koray Kavukcuoglu · 2016
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 2017
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Using the output embedding to improve language models, 2017
Ofir Press and Lior Wolf · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Vectornet: Encoding hd maps and agent dynamics from vectorized representation, 2020
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, and Cordelia Schmid · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi · 2020
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Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurélien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, and Dragomir Anguelov · 2021
Flashattention: Fast and memory-efficient exact attention with io-awareness, 2022
Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Symphony: Learning realistic and diverse agents for autonomous driving simulation, 2022
Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, and Shimon Whiteson · 2022
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Wayformer: Motion forecasting via simple and efficient attention networks, 2022
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, and Benjamin Sapp · 2022
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Motion transformer with global intention localization and local movement refinement
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2022
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Guided conditional diffusion for controllable traffic simulation, 2022
Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, and Marco Pavone · 2022
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Lora: Low-rank adaptation of large language models
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Offline reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine · 2021
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Scene transformer: A unified multi-task model for behavior prediction and planning
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, David Weiss, Benjamin Sapp, Zhifeng Chen, and Jonathon Shlens · 2021
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Generating useful accident-prone driving scenarios via a learned traffic prior
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Trafficsim: Learning to simulate realistic multi-agent behaviors, 2021
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi-Pang Lam, Dragomir Anguelov, and Benjamin Sapp · 2021
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Gaia-1: A generative world model for autonomous driving, 2023
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
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Motiondiffuser: Controllable multi-agent motion prediction using diffusion, 2023
Chiyu Max Jiang, Andre Cornman, Cheolho Park, Ben Sapp, Yin Zhou, and Dragomir Anguelov · 2023
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Imitation is not enough: Robustifying imitation with reinforcement learning for challenging driving scenarios, 2023
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The waymo open sim agents challenge, 2023
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nick Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, and Dragomir Anguelov · 2023
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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
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Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying
Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2023
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