Fetching the paper…
Reading the bibliography…
Autonomous Driving (AD) encounters significant safety hurdles in long-tail unforeseen driving scenarios, largely stemming from the non-interpretability and poor generalization of the deep neural networks within the AD system, particularly in out-of-distribution and uncertain data.
Barrier certificates for nonlinear model validation
Stephen Prajna · 2006
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Hierarchical model predictive control for multi-robot navigation
Chao Huang, Xin Chen, Yifan Zhang, Shengchao Qin, Yifeng Zeng, and Xuandong Li · 2016
Earlier work this paper cites.
Data-driven computation of minimal robust control invariant set
Yuxiao Chen, Huei Peng, Jessy Grizzle, and Necmiye Ozay · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
An environment for autonomous driving decision-making
Edouard Leurent · 2018
Earlier work this paper cites.
Control barrier functions: Theory and applications
Aaron D Ames, Samuel Coogan, Magnus Egerstedt, Gennaro Notomista, Koushil Sreenath, and Paulo Tabuada · 2019
Earlier work this paper cites.
Reachnn: Reachability analysis of neural-network controlled systems
Chao Huang, Jiameng Fan, Wenchao Li, Xin Chen, and Qi Zhu · 2019
Earlier work this paper cites.
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein, Claudius Glaeser, Fabian Timm, Werner Wiesbeck, and Klaus Dietmayer · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Neural certificates for safe control policies
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou · 2020
Earlier work this paper cites.
Chatgpt-3: Language model for conversational agents
OpenAI · 2020
Earlier work this paper cites.
Energy-efficient control adaptation with safety guarantees for learning-enabled cyber-physical systems
Yixuan Wang, Chao Huang, and Qi Zhu · 2020
Earlier work this paper cites.
Verisig 2.0: Verification of neural network controllers using taylor model preconditioning
Radoslav Ivanov, Taylor Carpenter, James Weimer, Rajeev Alur, George Pappas, and Insup Lee · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Safe nonlinear control using robust neural lyapunov-barrier functions
Charles Dawson, Zengyi Qin, Sicun Gao, and Chuchu Fan · 2022
Cited alongside, same era.
Rino: robust inner and outer approximated reachability of neural networks controlled systems
Eric Goubault and Sylvie Putot · 2022
Cited alongside, same era.
Polar: A polynomial arithmetic framework for verifying neural-network controlled systems
Chao Huang, Jiameng Fan, Xin Chen, Wenchao Li, and Qi Zhu · 2022
Cited alongside, same era.
Tae: A semi-supervised controllable behavior-aware trajectory generator and predictor
Ruochen Jiao, Xiangguo Liu, Bowen Zheng, Dave Liang, and Qi Zhu · 2022
Cited alongside, same era.
Verification of neural-network control systems by integrating taylor models and zonotopes
Christian Schilling, Marcelo Forets, and Sebastián Guadalupe · 2022
Cited alongside, same era.
Gpt-driver: Learning to drive with gpt
Jiageng Mao, Yuxi Qian, Hang Zhao, and Yue Wang · 2023
Closest in time.
Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S Refaat, and Benjamin Sapp · 2023
Closest in time.
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
Closest in time.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Closest in time.
Joint differentiable optimization and verification for certified reinforcement learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Differentiable safe controller design through control barrier functions
Shuo Yang, Shaoru Chen, Victor M Preciado, and Rahul Mangharam · 2022
Cited alongside, same era.
Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, and Ziran Wang · 2023
Cited alongside, same era.
Magicdrive: Street view generation with diverse 3d geometry control
Ruiyuan Gao, Kai Chen, Enze Xie, Lanqing Hong, Zhenguo Li, Dit-Yan Yeung, and Qiang Xu · 2023
Cited alongside, same era.
Gaia-1: A generative world model for autonomous driving
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
Cited alongside, same era.
Learning representation for anomaly detection of vehicle trajectories
Ruochen Jiao, Juyang Bai, Xiangguo Liu, Takami Sato, Xiaowei Yuan, Qi Alfred Chen, and Qi Zhu · 2023
Cited alongside, same era.
Provably safe reinforcement learning via action projection using reachability analysis and polynomial zonotopes
Niklas Kochdumper, Hanna Krasowski, Xiao Wang, Stanley Bak, and Matthias Althoff · 2023
Cited alongside, same era.
Yixuan Wang, Simon Zhan, Zhilu Wang, Chao Huang, Zhaoran Wang, Zhuoran Yang, and Qi Zhu · 2023
Closest in time.
Lingo: Natural language for autonomous driving, 2023
Wayve · 2023
Closest in time.
Dilu: A knowledge-driven approach to autonomous driving with large language models
Licheng Wen, Daocheng Fu, Xin Li, Xinyu Cai, Tao Ma, Pinlong Cai, Min Dou, Botian Shi, Liang He, and Yu Qiao · 2023
Closest in time.
Language prompt for autonomous driving
Dongming Wu, Wencheng Han, Tiancai Wang, Yingfei Liu, Xiangyu Zhang, and Jianbing Shen · 2023
Closest in time.
Drivegpt4: Interpretable end-to-end autonomous driving via large language model
Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kenneth KY Wong, Zhenguo Li, and Hengshuang Zhao · 2023
Closest in time.
A survey of large language models for autonomous driving
Zhenjie Yang, Xiaosong Jia, Hongyang Li, and Junchi Yan · 2023
Closest in time.
State-wise safe reinforcement learning with pixel observations
Simon Sinong Zhan, Yixuan Wang, Qingyuan Wu, Ruochen Jiao, Chao Huang, and Qi Zhu · 2023
Closest in time.
Trafficgpt: Viewing, processing and interacting with traffic foundation models
Siyao Zhang, Daocheng Fu, Zhao Zhang, Bin Yu, and Pinlong Cai · 2023
Closest in time.
Language-guided traffic simulation via scene-level diffusion
Ziyuan Zhong, Davis Rempe, Yuxiao Chen, Boris Ivanovic, Yulong Cao, Danfei Xu, Marco Pavone, and Baishakhi Ray · 2023
Closest in time.
Vision language models in autonomous driving and intelligent transportation systems
Xingcheng Zhou, Mingyu Liu, Bare Luka Zagar, Ekim Yurtsever, and Alois C Knoll · 2023
Closest in time.
Drive like a human: Rethinking autonomous driving with large language models
Daocheng Fu, Xin Li, Licheng Wen, Min Dou, Pinlong Cai, Botian Shi, and Yu Qiao · 2024
Closest in time.