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Large Language Models (LLMs) have shown significant promise in real-world decision-making tasks for embodied artificial intelligence, especially when fine-tuned to leverage their inherent common sense and reasoning abilities while being tailored to specific applications.
Vision Meets Robotics: The Kitti Dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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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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An Environment for Autonomous Driving Decision-Making
Edouard Leurent · 2018
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Trojaning Attack on Neural Networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2018
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Virtualhome: Simulating household activities via programs
Xavier Puig, Kevin Ra, Marko Boben, Jiaman Li, Tingwu Wang, Sanja Fidler, and Antonio Torralba · 2018
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Scenic: A Language for Scenario Specification and Scene Generation
Daniel J Fremont, Tommaso Dreossi, Shromona Ghosh, Xiangyu Yue, Alberto L Sangiovanni-Vincentelli, and Sanjit A Seshia · 2019
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Sentence-Bert: Sentence Embeddings Using Siamese Bert-Networks
Nils Reimers and Iryna Gurevych · 2019
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Huggingface’s Transformers: State-of-the-Art Natural Language Processing
T Wolf · 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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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 · 2020
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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
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Know the unknowns: Addressing disturbances and uncertainties in autonomous systems
Qi Zhu, Wenchao Li, Hyoseung Kim, Yecheng Xiang, Kacper Wardega, Zhilu Wang, Yixuan Wang, Hengyi Liang, Chao Huang, Jiameng Fan, and Hyunjong Choi · 2020
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ONION: A Simple and Effective Defense Against Textual Backdoor Attacks
Fanchao Qi, Yangyi Chen, Mukai Li, Yuan Yao, Zhiyuan Liu, and Maosong Sun · 2021
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Data Augmentation can Improve Robustness
Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, and Timothy A Mann · 2021
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Safety-Assured Design and Adaptation of Learning-Enabled Autonomous Systems
Qi Zhu, Chao Huang, Ruochen Jiao, Shuyue Lan, Hengyi Liang, Xiangguo Liu, Yixuan Wang, Zhilu Wang, and Shichao Xu · 2021
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LoRA: Low-Rank Adaptation of Large Language Models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch · 2022
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The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns Via Spotlights of Attention
Kazuki Irie, Róbert Csordás, and Jürgen Schmidhuber · 2022
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TAE: A Semi-Supervised Controllable Behavior-Aware Trajectory Generator and Predictor
Ruochen Jiao, Xiangguo Liu, Bowen Zheng, Dave Liang, and Qi Zhu · 2022
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Training Language Models to Follow Instructions with Human Feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: A Survey
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, and Animesh Garg · 2023
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LLM-planner: Few-shot Grounded Planning for Embodied Agents with Large Language Models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
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Poisoning Language Models During Instruction Tuning
Alexander Wan, Eric Wallace, Sheng Shen, and Dan Klein · 2023
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Language Prompt for Autonomous Driving
Dongming Wu, Wencheng Han, Tiancai Wang, Yingfei Liu, Xiangyu Zhang, and Jianbing Shen · 2023
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A Survey of Large Language Models for Autonomous Driving
Zhenjie Yang, Xiaosong Jia, Hongyang Li, and Junchi Yan · 2023
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Cited alongside, same era.
Large Language Models for Autonomous Driving: Real-World Experiments
Can Cui, Zichong Yang, Yupeng Zhou, Yunsheng Ma, Juanwu Lu, and Ziran Wang · 2023
Cited alongside, same era.
Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers
Damai Dai, Yutao Sun, Li Dong, Yaru Hao, Shuming Ma, Zhifang Sui, and Furu Wei · 2023
Cited alongside, same era.
Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
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Semi-Supervised Semantics-Guided Adversarial Training for Robust Trajectory Prediction
Ruochen Jiao, Xiangguo Liu, Takami Sato, Qi Alfred Chen, and Qi Zhu · 2023
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Code as Policies: Language Model Programs for Embodied Control
Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, and Andy Zeng · 2023
Cited alongside, same era.
Dolphins: Multimodal Language Model for Driving
Yingzi Ma, Yulong Cao, Jiachen Sun, Marco Pavone, and Chaowei Xiao · 2023
Cited alongside, same era.
BEV-Guided Multi-Modality Fusion for Driving Perception
Yunze Man, Liang-Yan Gui, and Yu-Xiong Wang · 2023
Cited alongside, same era.
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RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, et al · 2023
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Talk2BEV: Language-Enhanced Bird’s-Eye View Maps for Autonomous Driving
Tushar Choudhary, Vikrant Dewangan, Shivam Chandhok, Shubham Priyadarshan, Anushka Jain, Arun K Singh, Siddharth Srivastava, Krishna Murthy Jatavallabhula, and K Madhava Krishna · 2024
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Copal: corrective planning of robot actions with large language models
Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker, Joerg Deigmoeller, Anna Belardinelli, Chao Wang, Stephan Hasler, Daniel Tanneberg, and Michael Gienger · 2024
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Driving Everywhere with Large Language Model Policy Adaptation
Boyi Li, Yue Wang, Jiageng Mao, Boris Ivanovic, Sushant Veer, Karen Leung, and Marco Pavone · 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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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 · 2024
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ChatGPT for Robotics: Design Principles and Model Abilities
Sai H Vemprala, Rogerio Bonatti, Arthur Bucker, and Ashish Kapoor · 2024
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Jailbroken: How Does LLM Safety Training Fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt · 2024
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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 · 2024
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BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models
Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, and Bo Li · 2024
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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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Watch Out for Your Agents! Investigating Backdoor Threats to LLM-based Agents
Wenkai Yang, Xiaohan Bi, Yankai Lin, Sishuo Chen, Jie Zhou, and Xu Sun · 2024
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Jianhao Yuan, Shuyang Sun, Daniel Omeiza, Bo Zhao, Paul Newman, Lars Kunze, and Matthew Gadd · 2024
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Poisonedrag: Knowledge Poisoning Attacks to Retrieval-Augmented Generation of Large Language Models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia · 2024
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