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Simulating realistic behaviors of traffic agents is pivotal for efficiently validating the safety of autonomous driving systems.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1988
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Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
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Sumo (simulation of urban mobility)-an open-source traffic simulation
Daniel Krajzewicz, Georg Hertkorn, Christian Rössel, and Peter Wagner · 2002
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General lane-changing model mobil for car-following models
Arne Kesting, Martin Treiber, and Dirk Helbing · 2007
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A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Japanese and korean voice search
Mike Schuster and Kaisuke Nakajima · 2012
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Learning phrase representations using rnn encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Argoverse: 3d tracking and forecasting with rich maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, et al · 2019
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Causal confusion in imitation learning
Pim De Haan, Dinesh Jayaraman, and Sergey Levine · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 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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wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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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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Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Vectornet: Encoding hd maps and agent dynamics from vectorized representation
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, and Cordelia Schmid · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Simnet: Learning reactive self-driving simulations from real-world observations
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Błażej Osiński, Hugo Grimmett, and Peter Ondruska · 2021
Cited alongside, same era.
Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, and Philipp Krähenbühl · 2021
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, and Jakob Nicolaus Foerster · 2022
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Hivt: Hierarchical vector transformer for multi-agent motion prediction
Zikang Zhou, Luyao Ye, Jianping Wang, Kui Wu, and Kejie Lu · 2022
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Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding
Xiaosong Jia, Penghao Wu, Li Chen, Yu Liu, Hongyang Li, and Junchi Yan · 2023
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The waymo open sim agents challenge
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Zeyu Yang, Shimon Whiteson, Brandyn White, and Dragomir Anguelov · 2023
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Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S Refaat, and Benjamin Sapp · 2023
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Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Cited alongside, same era.
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, et al · 2021
Cited alongside, same era.
Densetnt: End-to-end trajectory prediction from dense goal sets
Junru Gu, Chen Sun, and Hang Zhao · 2021
Cited alongside, same era.
Hubert: Self-supervised speech representation learning by masked prediction of hidden units
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed · 2021
Cited alongside, same era.
Drivergym: Democratising reinforcement learning for autonomous driving
Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, and Peter Ondruska · 2021
Cited alongside, same era.
Trafficsim: Learning to simulate realistic multi-agent behaviors
Simon Suo, Sebastian Regalado, Sergio Casas, and Raquel Urtasun · 2021
Cited alongside, same era.
A time series is worth 64 words: Long-term forecasting with transformers
Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam · 2023
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Motionlm: Multi-agent motion forecasting as language modeling
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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Multiverse transformer: 1st place solution for waymo open sim agents challenge 2023
Yu Wang, Tiebiao Zhao, and Fan Yi · 2023
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Bits: Bi-level imitation for traffic simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone · 2023
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Unisim: A neural closed-loop sensor simulator
Ze Yang, Yun Chen, Jingkang Wang, Sivabalan Manivasagam, Wei-Chiu Ma, Anqi Joyce Yang, and Raquel Urtasun · 2023
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Real-time motion prediction via heterogeneous polyline transformer with relative pose encoding
Zhejun Zhang, Alexander Liniger, Christos Sakaridis, Fisher Yu, and Luc Van Gool · 2023
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Guided conditional diffusion for controllable traffic simulation
Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Tong Che, Baishakhi Ray, and Marco Pavone · 2023
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Query-centric trajectory prediction
Zikang Zhou, Jianping Wang, Yung-Hui Li, and Yu-Kai Huang · 2023
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Better & faster large language models via multi-token prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière, David Lopez-Paz, and Gabriel Synnaeve · 2024
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Solving motion planning tasks with a scalable generative model
Yihan Hu, Siqi Chai, Zhening Yang, Jingyu Qian, Kun Li, Wenxin Shao, Haichao Zhang, Wei Xu, and Qiang Liu · 2024
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Versatile scene-consistent traffic scenario generation as optimization with diffusion
Zhiyu Huang, Zixu Zhang, Ameya Vaidya, Yuxiao Chen, Chen Lv, and Jaime Fernández Fisac · 2024
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Trajeglish: Traffic modeling as next-token prediction
Jonah Philion, Xue Bin Peng, and Sanja Fidler · 2024
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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 · 2024
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Zhejun Zhang, Christos Sakaridis, and Luc Van Gool · 2024
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