Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) are demonstrating outstanding potential for tasks such as text generation, summarization, and classification.
Openweather: Weather forecasts, nowcasts and history in a fast and elegant way, 2012
OpenWeather · 2012
Earlier work this paper cites.
Defining and substantiating the terms scene, situation, and scenario for automated driving
Simon Ulbrich, Till Menzel, Andreas Reschka, Fabian Schuldt, and Markus Maurer · 2015
Earlier work this paper cites.
Testing vision-based control systems using learnable evolutionary algorithms
Raja Ben Abdessalem, Shiva Nejati, Lionel C Briand, and Thomas Stifter · 2018
Earlier work this paper cites.
Testing autonomous cars for feature interaction failures using many-objective search
Raja Ben Abdessalem, Annibale Panichella, Shiva Nejati, Lionel C Briand, and Thomas Stifter · 2018
Earlier work this paper cites.
Generating effective test cases for self-driving cars from police reports
Alessio Gambi, Tri Huynh, and Gordon Fraser · 2019
Earlier work this paper cites.
Scenario based testing of automated driving systems: A literature survey
Demin Nalic, Tomislav Mihalj, Maximilian Bäumler, Matthias Lehmann, Arno Eichberger, and Stefan Bernsteiner · 2020
Earlier work this paper cites.
Generating avoidable collision scenarios for testing autonomous driving systems
Alessandro Calò, Paolo Arcaini, Shaukat Ali, Florian Hauer, and Fuyuki Ishikawa · 2020
Earlier work this paper cites.
Av-fuzzer: Finding safety violations in autonomous driving systems
Guanpeng Li, Yiran Li, Saurabh Jha, Timothy Tsai, Michael Sullivan, Siva Kumar Sastry Hari, Zbigniew Kalbarczyk, and Ravishankar Iyer · 2020
Earlier work this paper cites.
Av-fuzzer: Finding safety violations in autonomous driving systems
Guanpeng Li, Yiran Li, Saurabh Jha, Timothy Tsai, Michael Sullivan, Siva Kumar Sastry Hari, Zbigniew Kalbarczyk, and Ravishankar Iyer · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Studying the usage of text-to-text transfer transformer to support code-related tasks
Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader Palacio, Denys Poshyvanyk, Rocco Oliveto, and Gabriele Bavota · 2021
Earlier work this paper cites.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Earlier work this paper cites.
Adversarial evaluation of autonomous vehicles in lane-change scenarios
Baiming Chen, Xiang Chen, Qiong Wu, and Liang Li · 2022
Earlier work this paper cites.
Learning configurations of operating environment of autonomous vehicles to maximize their collisions
Chengjie Lu, Yize Shi, Huihui Zhang, Man Zhang, Tiexin Wang, Tao Yue, and Shaukat Ali · 2022
Earlier work this paper cites.
Risk Assessment of Highly Automated Vehicles with Naturalistic Driving Data: A Surrogate-based optimization Method
He Zhang, Huajun Zhou, Jian Sun, and Ye Tian · 2022
Earlier work this paper cites.
Prcbert: Prompt learning for requirement classification using bert-based pretrained language models
Xianchang Luo, Yinxing Xue, Zhenchang Xing, and Jiamou Sun · 2022
Earlier work this paper cites.
A systematic evaluation of large language models of code
Frank F Xu, Uri Alon, Graham Neubig, and Vincent Josua Hellendoorn · 2022
Earlier work this paper cites.
A survey on automated driving system testing: Landscapes and trends
Shuncheng Tang, Zhenya Zhang, Yi Zhang, Jixiang Zhou, Yan Guo, Shuang Liu, Shengjian Guo, Yan-Fu Li, Lei Ma, Yinxing Xue, and Yang Liu · 2023
Earlier work this paper cites.
Finding critical scenarios for automated driving systems: A systematic mapping study
Xinhai Zhang, Jianbo Tao, Kaige Tan, Martin Törngren, José Manuel Gaspar Sánchez, Muhammad Rusyadi Ramli, Xin Tao, Magnus Gyllenhammar, Franz Wotawa, Naveen Mohan, Mihai Nica, and Hermann Felbinger · 2023
Earlier work this paper cites.
Dense reinforcement learning for safety validation of autonomous vehicles
Shuo Feng, Haowei Sun, Xintao Yan, Haojie Zhu, Zhengxia Zou, Shengyin Shen, and Henry X Liu · 2023
Earlier work this paper cites.
Many-objective reinforcement learning for online testing of dnn-enabled systems
Fitash Ul Haq, Donghwan Shin, and Lionel C. Briand · 2023
Cited alongside, same era.
Causality-driven testing of autonomous driving systems
Luca Giamattei, Antonio Guerriero, Roberto Pietrantuono, and Stefano Russo · 2023
Cited alongside, same era.
Mind the gap! a study on the transferability of virtual versus physical-world testing of autonomous driving systems
Andrea Stocco, Brian Pulfer, and Paolo Tonella · 2023
Cited alongside, same era.
Deepqtest: Testing autonomous driving systems with reinforcement learning and real-world weather data, 2023
Chengjie Lu, Tao Yue, Man Zhang, and Shaukat Ali · 2023
Cited alongside, same era.
Learning naturalistic driving environment with statistical realism
Xintao Yan, Zhengxia Zou, Shuo Feng, Haojie Zhu, Haowei Sun, and Henry X Liu · 2023
Cited alongside, same era.
Software testing with large language model: Survey, landscape, and vision
Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, and Qing Wang · 2023
Later among the works it cites.
Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models
Caroline Lemieux, Jeevana Priya Inala, Shuvendu K. Lahiri, and Siddhartha Sen · 2023
Later among the works it cites.
Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Xing Che, Dandan Wang, and Qing Wang · 2023
Later among the works it cites.
A preliminary evaluation of chatgpt in requirements information retrieval
Jianzhang Zhang, Yiyang Chen, Nan Niu, and Chuang Liu · 2023
Later among the works it cites.
Llm is like a box of chocolates: the non-determinism of chatgpt in code generation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Llm4drive: A survey of large language models for autonomous driving, 2023
Zhenjie Yang, Xiaosong Jia, Hongyang Li, and Junchi Yan · 2023
Cited alongside, same era.
A survey on multimodal large language models for autonomous driving, 2023
Can Cui, Yunsheng Ma, Xu Cao, Wenqian Ye, Yang Zhou, Kaizhao Liang, Jintai Chen, Juanwu Lu, Zichong Yang, Kuei-Da Liao, Tianren Gao, Erlong Li, Kun Tang, Zhipeng Cao, Tong Zhou, Ao Liu, Xinrui Yan, Shuqi Mei, Jianguo Cao, Ziran Wang, and Chao Zheng · 2023
Cited alongside, same era.
Gpt 3.5, 2023
OpenAI · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Cited alongside, same era.
Deepscenario: An open driving scenario dataset for autonomous driving system testing
Chengjie Lu, Tao Yue, and Shaukat Ali · 2023
Cited alongside, same era.
Lawbreaker: An approach for specifying traffic laws and fuzzing autonomous vehicles
Yang Sun, Christopher M. Poskitt, Jun Sun, Yuqi Chen, and Zijiang Yang · 2023
Cited alongside, same era.
Shuyin Ouyang, Jie M Zhang, Mark Harman, and Meng Wang · 2023
Later among the works it cites.
Look before you leap: An exploratory study of uncertainty measurement for large language models
Yuheng Huang, Jiayang Song, Zhijie Wang, Huaming Chen, and Lei Ma · 2023
Later among the works it cites.
Language prompt for autonomous driving, 2023
Dongming Wu, Wencheng Han, Tiancai Wang, Yingfei Liu, Xiangyu Zhang, and Jianbing Shen · 2023
Later among the works it cites.
Hilm-d: Towards high-resolution understanding in multimodal large language models for autonomous driving, 2023
Xinpeng Ding, Jianhua Han, Hang Xu, Wei Zhang, and Xiaomeng Li · 2023
Later among the works it cites.
Can you text what is happening? integrating pre-trained language encoders into trajectory prediction models for autonomous driving, 2023
Ali Keysan, Andreas Look, Eitan Kosman, Gonca Gürsun, Jörg Wagner, Yu Yao, and Barbara Rakitsch · 2023
Later among the works it cites.
Mtd-gpt: A multi-task decision-making gpt model for autonomous driving at unsignalized intersections, 2023
Jiaqi Liu, Peng Hang, Xiao qi, Jianqiang Wang, and Jian Sun · 2023
Later among the works it cites.
Languagempc: Large language models as decision makers for autonomous driving, 2023
Hao Sha, Yao Mu, Yuxuan Jiang, Li Chen, Chenfeng Xu, Ping Luo, Shengbo Eben Li, Masayoshi Tomizuka, Wei Zhan, and Mingyu Ding · 2023
Later among the works it cites.
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
Later among the works it cites.
Proto-clip: Vision-language prototypical network for few-shot learning, 2023
Jishnu Jaykumar P, Kamalesh Palanisamy, Yu-Wei Chao, Xinya Du, and Yu Xiang · 2023
Later among the works it cites.
Multimodality helps unimodality: Cross-modal few-shot learning with multimodal models
Zhiqiu Lin, Samuel Yu, Zhiyi Kuang, Deepak Pathak, and Deva Ramanan · 2023
Later among the works it cites.
Drivegpt4: Interpretable end-to-end autonomous driving via large language model, 2023
Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kwan-Yee. K. Wong, Zhenguo Li, and Hengshuang Zhao · 2023
Later among the works it cites.
Target: Automated scenario generation from traffic rules for testing autonomous vehicles, 2023
Yao Deng, Jiaohong Yao, Zhi Tu, Xi Zheng, Mengshi Zhang, and Tianyi Zhang · 2023
Later among the works it cites.
Parameter coverage for testing of autonomous driving systems under uncertainty
Thomas Laurent, Stefan Klikovits, Paolo Arcaini, Fuyuki Ishikawa, and Anthony Ventresque · 2023
Later among the works it cites.
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.
Jiahui Wu, Chengjie Lu, Aitor Arrieta, Tao Yue, and Shaukat Ali · 2024
Closest in time.