Chen J , Sun J and Wang G 2022 From unmanned systems to autonomous intelligent systems Engineering 12 16 – 19

Leikas J , Koivisto R and Gotcheva N 2019 Ethical framework for designing autonomous intelligent systems J. Open Innov. 5 18

Long L N , Hanford S D , Janrathitikarn O , Sinsley G L and Miller J A 2007 A review of intelligent systems software for autonomous vehicles 2007 IEEE Symp. on Computational Intelligence in Security and Defense Applications ( IEEE ) pp 69 – 76

Chen Y , Chen S , Zhang T , Zhang S and Zheng N 2018 Autonomous vehicle testing and validation platform: Integrated simulation system with hardware in the loop 2018 IEEE Intelligent Vehicles Symp. (IV) ( IEEE ) pp 949 – 56

Illiashenko O , Kharchenko V , Babeshko I , Fesenko H and Di Giandomenico F 2023 Security-informed safety analysis of autonomous transport systems considering AI-powered cyberattacks and protection Entropy 25 1123

Aghababaeyan Z , Abdellatif M , Briand L , Ramesh S and Bagherzadeh M 2023 Black-box testing of deep neural networks through test case diversity IEEE Trans. Softw. Eng. 49 3182 – 204

Păsăreanu C S , Gopinath D and Yu H 2019 Compositional verification for autonomous systems with deep learning components: white paper Safe, Autonomous and Intelligent Vehicles pp 187 – 97

Wang H , Li Y-F and Ren J 2024 Machine learning for fault diagnosis of high-speed train traction systems: a review Front. Eng. Manage. 11 62 – 78

Dennis L A , Fisher M , Lincoln N K , Lisitsa A and Veres S M 2016 Practical verification of decision-making in agent-based autonomous systems Autom. Softw. Eng. 23 305 – 59

Zheng D , Fu X , Liu X , Xing L and Peng R 2024 Modeling and analysis of cascading failures in industrial internet of things considering sensing-control flow and service community IEEE Trans. Reliab. 74 2723 – 37

Li D , Wang H and Li Y-F 2024 Robust anomaly detection in unmanned ship systems based on large language models ESREL 2024 Collection of Extended Abstracts Part 1 p 47

Liu Y et al 2023 Summary of ChatGPT-related research and perspective towards the future of large language models Meta-Radiology 1 100017

Collins K M , Wong C , Feng J , Wei M and Tenenbaum J B 2022 Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks (arXiv:2205.05718)

Xie C and Zou D 2024 A human-like reasoning framework for multi-phases planning task with large language models (arXiv:2405.18208)

Hagendorff T , Fabi S and Kosinski M 2023 Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT Nat. Comput. Sci. 3 833 – 8

Li D , Wang H , Lin R , Li Y , Ye J , Miao D , Lin K and Zhang H 2024 Pretrained large models in telecommunications: a survey of technologies and applications 2024 IEEE Int. Conf. on Progress in Informatics and Computing (PIC) ( IEEE ) pp 117 – 21

Li Y , Katsumata K , Javanmardi E and Tsukada M 2024 Large language models for human-like autonomous driving: a survey 2024 IEEE 27th Int. Conf. on Intelligent Transportation Systems (ITSC) ( IEEE ) pp 439 – 46

Tian H , Reddy K , Feng Y , Quddus M , Demiris Y and Angeloudis P 2024 Large (vision) language models for autonomous vehicles: current trends and future directions IEEE Trans. Intell. Transp. Syst. 27 187 – 210

Chatila R and Havens J C 2019 The IEEE global initiative on ethics of autonomous and intelligent systems Robotics and Well-Being pp 11 – 6

Acharya D B , Kuppan K and Divya B 2025 Agentic AI: autonomous intelligence for complex goals–a comprehensive survey IEEE Access 13 18912 – 36

Pandey A K and Roy S S 2024 Extractive question answering over ancient scriptures texts using generative AI and natural language processing techniques IEEE Access 12 101197 – 209

Achiam J et al 2023 Gpt-4 technical report (arXiv:2303.08774)

Google DeepMind Team 2024 Introducing Gemini 2.0: the next generation of multimodal AI models (available at: https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/ https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/ ) (Accessed 23 October 2025 )

Anthropic 2024 https://www.anthropic.com/news/claude-3-family https://www.anthropic.com/news/claude-3-family (Accessed 19 March 2026 ) Introducing the next generation of Claude

Liu A et al 2024 Deepseek-v2: a strong, economical, and efficient mixture-of-experts language model (arXiv:2405.04434)

Liu A et al 2024 Deepseek-v3 technical report (arXiv:2412.19437)

Wu Z et al 2024 Deepseek-vl2: mixture-of-experts vision-language models for advanced multimodal understanding (arXiv:2412.10302)

xAI Team 2024 Grok 1.5: advancing reasoning and efficiency in the xAI model family (available at: https://x.ai/news/grok-1.5 https://x.ai/news/grok-1.5 ) (Accessed 23 October 2025 )

Jiang A Q et al 2024 Mixtral of experts (arXiv:2401.04088)

Meta AI Research Team 2024 The llama 3 herd of models (available at: https://ai.meta.com/research/publications/the-llama-3-herd-of-models/ https://ai.meta.com/research/publications/the-llama-3-herd-of-models/ ) (Accessed 23 October 2025 )

Hui B et al 2024 Qwen2.5-coder technical report (arXiv:2409.12186)

Bai S et al 2025 Qwen2.5-vl technical report (arXiv:2502.13923)

Zhou H et al 2024 Large language model (11m) for telecommunications: a comprehensive survey on principles, key techniques and opportunities IEEE Commun. Surv. Tutor. 27 1955 – 2005

Zhang H et al 2024 A careful examination of large language model performance on grade school arithmetic Advances in Neural Information Processing Systems vol 37 pp 46819 – 36

Li Y-F , Wang H and Sun M 2024 ChatGPT-like large-scale foundation models for prognostics and health management: a survey and roadmaps Reliab. Eng. Syst. Saf. 243 109850

Clarke E , Garlan D , Krogh B , Simmons R and Wing J 2001 Formal verification of autonomous systems NASA intelligent systems program

Ruospo A , Cantoro R , Sanchez E , Schiavone P D , Garofalo A and Benini L 2019 On-line testing for autonomous systems driven by risc-v processor design verification 2019 IEEE Int. Symp. on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT) ( IEEE ) pp 1 – 6

Ferrando A , Dennis L A , Ancona D , Fisher M and Mascardi V 2018 Verifying and validating autonomous systems: towards an integrated approach Runtime Verification: 18th Int. Conf., RV 2018, (Limassol, Cyprus, 10 November–13 November 2018) ( Proc. 18 ) ( Springer ) pp 263 – 81

Wang X , Guo Y and Gao Y 2024 Unmanned autonomous intelligent system in 6g non-terrestrial network Information 15 38

Sandhya Devi R S and Varshni S D 2025 Embedded large language models for enhanced human-machine interface in autonomous vehicles 2025 Int. Conf. on Multi-Agent Systems for Collaborative Intelligence (ICMSCI) ( IEEE ) pp 1143 – 50

Thapa S and Adhikari S 2024 Leveraging ChatGPT-like large language models for Alzheimer's disease: enhancing care, advancing research and overcoming challenges Smart Healthcare Systems ( CRC Press ) pp 265 – 75

Yang Y , Zhang Q , Li Ci , Simões Marta D , Batool N and Folkesson J 2024 Human-centric autonomous systems with LLMs for user command reasoning Proc. IEEE/CVF Winter Conf. on Applications of Computer Vision pp 988 – 94

Mahmud D , Hajmohamed H , Almentheri S , Alqaydi S , Aldhaheri L , Khalil R A and Saeed N 2025 Integrating LLMs with its: recent advances, potentials, challenges and future directions IEEE Trans. Intell. Transp. Syst. 26 5674 – 709

Chang C , Wang S , Zhang J , Ge J and Li Li 2024 LLMScenario: large language model driven scenario generation IEEE Trans. Syst. Man Cybern. 54 6581 – 94

Tang S , Zhang Z , Zhou J , Lei L , Zhou Y and Xue Y 2024 Legend: a top-down approach to scenario generation of autonomous driving systems assisted by large language models Proc. 39th IEEE/ACM Int. Conf. on Automated Software Engineering pp 1497 – 508

González-Santamarta M A , Rodríguez-Lera F J , Manuel Guerrero-Higueras Angel and Matellán-Olivera V 2023 Integration of large language models within cognitive architectures for autonomous robots (arXiv:2309.14945)

Xu F F , Alon U , Neubig G and Hellendoorn V J 2022 A systematic evaluation of large language models of code Proc. 6th ACM SIGPLAN Int. Symp. on Machine Programming pp 1 – 10

Ma Y et al 2024 Lampilot: an open benchmark dataset for autonomous driving with language model programs Proc. IEEE/CVF Conf. on Computer Vision and Pattern Recognition pp 15141 – 51

Nouri A , Cabrero-Daniel B , Fei Z , Ronanki K , Sivencrona H and Berger C 2025 Large language models in code co-generation for safe autonomous vehicles (arXiv:2505.19658)

Luckcuck M 2023 Using formal methods for autonomous systems: five recipes for formal verification Proc. Inst. Mech. Eng. O 237 278 – 92

Grossberg S 2025 Neural network models of autonomous adaptive intelligence and artificial general intelligence: how our brains learn large language models and their meanings Front. Syst. Neurosci. 19 1630151

Lin Y , Wang X , Yang J and Wang S 2024 Core technology topic identification and evolution analysis based on patent text mining-a case study of unmanned ship Appl. Sci. 14 4661

Bhat A , Mondal A and Tripathy A 2025 LLM agents for Internet of Things (IoT) applications

Palin R , Ward D , Habli I and Rivett R 2011 Iso 26262 safety cases: compliance and assurance 6th IET Int. Conf. on System Safety 2011 ( IET ) p B12

Alaqail H and Ahmed S 2018 Overview of software testing standard ISO/IEC/IEEE 29119 Int. J. Comput. Sci. Netw. Secur. 18 112 – 6

Gosavi M A , Rhoades B B and Conrad J M 2018 Application of functional safety in autonomous vehicles using iso 26262 standard: a survey SoutheastCon 2018 ( IEEE ) pp 1 – 6

Song Q , Engström E and Runeson P 2021 Concepts in testing of autonomous systems: Academic literature and industry practice 2021 IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN) ( IEEE ) pp 74 – 81

Madhavan R , Lakaemper R and Kalmár-Nagy T 2009 Benchmarking and standardization of intelligent robotic systems 2009 Int. Conf. on Advanced Robotics ( IEEE ) pp 1 – 7

Chen J and Lu S 2024 An advanced driving agent with the multimodal large language model for autonomous vehicles 2024 IEEE Int. Conf. on Mobility, Operations, Services and Technologies (MOST) ( IEEE ) pp 1 – 11

Sheng Z , Xu Q , Huang J , Woodcock M , Huang H , Donaldson A F , Gu G and Huang J 2025 All you need is a fuzzing brain: an LLM-powered system for automated vulnerability detection and patching (arXiv:2509.07225)

Cheng Y , Kang H J , Shar L K , Dong C , Shi Z , Lv S and Sun L 2025 Towards reliable LLM-driven fuzz testing: vision and road ahead (arXiv:2503.00795)

Black G , Vaidyan V and Comert G 2024 Evaluating large language models for enhanced fuzzing: an analysis framework for LLM-driven seed generation IEEE Access 12 156065 – 81

Ishida S , Corrado G , Fedoseev G , Yeo H , Russell L , Shotton J , Henriques J F and Hu A 2024 Langprop: a code optimization framework using large language models applied to driving ICLR 2024 Workshop on Large Language Model (LLM) Agents

Liang X , Song S , Zheng Z , Wang H , Yu Q , Li X , Li R-H , Xiong F and Li Z 2024 Internal consistency and self-feedback in large language models: a survey (arXiv:2407.14507)

Razdan R , ilhan Akbaş M , Sell R , Bellone M , Menase M and Malayjerdi M 2023 Polyverif: an open-source environment for autonomous vehicle validation and verification research acceleration IEEE Access 11 28343 – 54

Bandi A , Nukala H S T , Tatavarthi B and Boggavarapu A 2025 Automated test case generation for software testing using generative AI Int. Conf. on Computers and Their Applications ( Springer ) pp 78 – 87

Chen Y , Ye Y , Chen Z , Zhang C and Ang M H 2024 Aro: large language model supervised robotics text2skill autonomous learning (arXiv:2403.15834)

Li F , Wang X , Li B , Wu Y , Wang Y and Yi X 2024 A study on training and developing large language models for behavior tree generation (arXiv:2401.08089)

Mitra C , Miroyan M , Jain R , Kumud V , Ranade G and Norouzi N 2024 Retllm-e: retrieval-prompt strategy for question-answering on student discussion forums Proc. AAAI Conf. on Artificial Intelligence vol 38 pp 23215 – 23

Tian H , Reddy K , Feng Y , Quddus M , Demiris Y and Angeloudis P 2024 Enhancing autonomous vehicle training with language model integration and critical scenario generation (arXiv:2404.08570)

Wang J , Huang Y , Chen C , Liu Z , Wang S and Wang Q 2024 Software testing with large language models: survey, landscape and vision IEEE Trans. Softw. Eng. 50 911 – 36

Guo Z et al 2023 Evaluating large language models: a comprehensive survey (arXiv:2310.19736)

McIntosh T R , Susnjak T , Liu T , Watters P and Halgamuge M N 2024 Inadequacies of large language model benchmarks in the era of generative artificial intelligence (arXiv:2402.09880)

Chib P S and Singh P 2024 LG-Traj: LLM guided pedestrian trajectory prediction (arXiv:2403.08032)

Rasheed Z , Waseem M , Systä K and Abrahamsson P 2024 Large language model evaluation via multi AI agents: preliminary results (arXiv:2404.01023)

Su J , Jiang C , Jin X , Qiao Y , Xiao T , Ma H , Wei R , Jing Z , Xu J and Lin J 2024 Large language models for forecasting and anomaly detection: a systematic literature review (arXiv:2402.10350)

Merten G , Dejaegere G and Sakr M 2025 Using LLMs for analyzing AIS data (arXiv:2504.07557)

Tian X , Gu J , Li B , Liu Y , Hu C , Wang Y , Zhan K , Jia P , Lang X and Zhao H 2024 Drivevlm: the convergence of autonomous driving and large vision-language models (arXiv:2402.12289)

Xu Z , Zhang Y , Xie E , Zhao Z , Guo Y , Wong K-Y K , Li Z and Zhao H 2024 DriveGPT4: interpretable end-to-end autonomous driving via large language model IEEE Robot. Autom. Lett.

Xu Z , Bai Y , Zhang Y , Li Z , Xia F , Wong K-Y K , Wang J and Zhao H 2025 DriveGPT4-v2: harnessing large language model capabilities for enhanced closed-loop autonomous driving Proc. Computer Vision and Pattern Recognition Conf. pp 17261 – 70

Cui Y , Huang S , Zhong J , Liu Z , Wang Y , Sun C , Li B , Wang X and Khajepour A 2023 Drivellm: charting the path toward full autonomous driving with large language models IEEE Trans. Intell. Veh. 9 1450 – 64

Wen L , Fu D , Li X , Cai X , Ma T , Cai P , Dou M , Shi B , He L and Qiao Y 2023 Dilu: a knowledge-driven approach to autonomous driving with large language models (arXiv:2309.16292)

Katzourakis D 2025 Systems engineering for autonomous vehicles; supervising AI using large language models (ssuperllm) (arXiv:2501.10839)

Fu D , Li X , Wen L , Dou M , Cai P , Shi B and Qiao Y 2024 Drive like a human: rethinking autonomous driving with large language models 2024 IEEE/CVF Winter Conf. on Applications of Computer Vision Workshops (WACVW) ( IEEE ) pp 910 – 9

Cui C , Yang Z , Zhou Y , Ma Y , Lu J , Li L , Chen Y , Panchal J and Wang Z 2024 Personalized autonomous driving with large language models: field experiments 2024 IEEE 27th Int. Conf. on Intelligent Transportation Systems (ITSC) ( IEEE ) pp 20 – 27

Li Y , Li L , Wu Z , Bing Z , Ai Y , Tian B , Xuanyuan Z , Knoll A C and Chen L 2024 Miningllm: towards mining 5.0 via large language models in autonomous driving and smart mining IEEE Trans. Intell. Veh. 1 – 12

Ping Y et al 2025 Multimodal large language models-enabled UAV swarm: towards efficient and intelligent autonomous aerial systems (arXiv:2506.12710)

Sezgin A 2025 Scenario-driven evaluation of autonomous agents: Integrating large language model for UAV mission reliability Drones 9 213

Tagliabue A , Kondo K , Zhao T , Peterson M , Tewari C T and How J P 2024 Real: resilience and adaptation using large language models on autonomous aerial robots 2024 IEEE 63rd Conf. on Decision and Control (CDC) ( IEEE ) pp 1539 – 46

Duvvuru V S A , Zhang B , Vierhauser M and Agrawal A 2025 LLM-agents driven automated simulation testing and analysis of small uncrewed aerial systems (arXiv:2501.11864)

Sautenkov O , Yaqoot Y , Mustafa M A , Batool F , Sam J , Lykov A , Wen C-Y and Tsetserukou D 2025 UAV-CodeAgents: scalable UAV mission planning via multi-agent react and vision-language reasoning (arXiv:2505.07236)

Cai S , Wu Y and Zhou L 2025 LLM-land: large language models for context-aware drone landing (arXiv:2505.06399)

Wu W , Li C , Wang X , Luo B and Liu Q 2025 Large language model guided progressive feature alignment for multimodal UAV object detection (arXiv:2503.06948)

Cai H , Dong J , Tan J , Deng J , Li S , Gao Z , Wang H , Su Z , Sumalee A and Zhong R 2025 FlightGPT: towards generalizable and interpretable UAV vision-and-language navigation with vision-language models (arXiv:2505.12835)

Lin F , Tian Y , Wang Y , Zhang T , Zhang X and Wang F-Y 2024 Airvista: empowering UAVs with 3D spatial reasoning abilities through a multimodal large language model agent 2024 IEEE 27th Int. Conf. on Intelligent Transportation Systems (ITSC) ( IEEE ) pp 476 – 81

Yao F , Yue Y , Liu Y , Sun X and Fu K 2024 Aeroverse: UAV-agent benchmark suite for simulating, pre-training, finetuning, and evaluating aerospace embodied world models (arXiv:2408.15511)

Li H , Liu X and Li G 2024 A benchmark for UAV-view natural language-guided tracking Electronics 13 1706

Wen Z , Zhao J , Zhang A , Bi W , Kuang B , Su Y and Wang R 2025 BiDGCNLLM: a graph–language model for drone state forecasting and separation in urban air mobility using digital twin-augmented remote ID data Drones 9 508

Khatiri S , Di Sorbo A , Zampetti F , Visaggio C A , Di Penta M and Panichella S 2024 Identifying safety–critical concerns in unmanned aerial vehicle software platforms with salient SoftwareX 27 101748

Liu G , Sun T , Li W , Li X , Liu X and Cui J 2024 EAI-sim: an open-source embodied AI simulation framework with large language models 2024 IEEE 18th Int. Conf. on Control & Automation (ICCA) ( IEEE ) pp 994 – 9

Tasneem O and Pieters R 2026 Human–robot collaborative visual inspection with large language models Robot. Comput.-Integr. Manuf. 98 103154

Yang Z , Raman S S , Shah A and Tellex S 2024 Plug in the safety chip: enforcing constraints for LLM-driven robot agents 2024 IEEE Int. Conf. on Robotics and Automation (ICRA) ( IEEE ) pp 14435 – 42

Waseem M , Bhatta K , Li C and Chang Q 2025 Pretrained LLMs as real-time controllers for robot operated serial production line (arXiv:2503.03889)

Lykov A , Cabrera M A , Konenkov M , Serpiva V , Gbagbe K F , Alabbas A , Fedoseev A , Moreno L , Khan M H and Guo Z 2024 Industry 6.0: new generation of industry driven by generative AI and swarm of heterogeneous robots (arXiv:2409.10106)

Rema C , Sousa A , Sobreira H , Costa P and Silva M F 2025 Exploring the potential of LLM-based chatbots for task scheduling in robot operations 2025 IEEE Int. Conf. on Autonomous Robot Systems and Competitions (ICARSC) ( IEEE ) pp 45 – 51

Zhang X , Yuan K , Xia L , Ma L , Liu H , Zhang X and Lyu Z 2025 LLM closed-loop application framework for industry manipulator system Proc. 4th Int. Conf. on Computer, Artificial Intelligence and Control Engineering pp 492 – 8

Rekik K , Silva G , Bashir A and Müller R 2025 Multimodal interaction for human-robot collaboration in assembly: an LLM-enhanced approach 2025 IEEE 21st Int. Conf. on Automation Science and Engineering (CASE) ( IEEE ) pp 1207 – 12

Zhang C , Zhang C , Xu Z , Xie Q , Hou J , Feng P and Zeng L 2025 Embodied intelligent industrial robotics: concepts and techniques (arXiv:2505.09305)

Oyekan J , Turner C , Bax M and Graf E 2025 Applying ontologies and knowledge augmented large language models to industrial automation: a decision-making guidance for achieving human-robot collaboration in industry 5.0 (arXiv:2505.18553)

Xu C , Chu Y , Gao Q , Wu Z , Wang J , Yue Y , Dominik W and Zhu X 2025 Autonomous unmanned surface vehicle docking using large language model guide reinforcement learning Ocean Eng. 323 120608

Yang R , Hou M , Wang J and Zhang F 2023 Oceanchat: piloting autonomous underwater vehicles in natural language (arXiv:2309.16052)

Yang R , Zhang F and Hou M 2024 Oceanplan: Hierarchical planning and replanning for natural language auv piloting in large-scale unexplored ocean environments Proc. 18th Int. Conf. on Underwater Networks & Systems pp 1 – 5

Din M U , Akram W , Bakht A B , Dong Y and Hussain I 2025 Maritime mission planning for unmanned surface vessel using large language model 2025 IEEE Int. Conf. on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR) ( IEEE ) pp 1 – 6

Wen J , Li Z , Xi M and He J 2025 A LLM-assisted AUV 3D path planning scheme under ocean current interference via reinforcement learning IEEE Internet Things J. 12 39185 – 96

Zhang M , Kuang M , Shi H , Zhu J , Zhu J and Jiang X 2025 Command-agent: reconstructing warfare simulation and command decision-making using large language models Defence Technol. 56 294 – 313

Caissutti C , Gerbier E , Khorrambakht E , Marinelli P , Munafo A and Caiti A 2025 Shared autonomy through LLMs and reinforcement learning for applications to ship hull inspections (arXiv:2509.05042)

Grimaldi M , Cernicchiaro C , Rua S R , El-Masri-El-Chaarani A , Buchholz M , Michael L , Rodriguez P R , Carlucho I and Petillot Y R 2025 Advancing shared and multi-agent autonomy in underwater missions: integrating knowledge graphs and retrieval-augmented generation (arXiv:2507.20370)

Saad A , Akram W and Hussain I 2025 Aquachat++: LLM-assisted multi-ROV inspection for aquaculture net pens with integrated battery management and thruster fault tolerance (arXiv:2508.06554)

Chen R , Blow D , Abdullah A and Islam Md J 2025 Word2wave: language driven mission programming for efficient subsea deployments of marine robots 2025 IEEE Int. Conf. on Robotics and Automation (ICRA) ( IEEE ) pp 4107 – 14

Zhang W , Cai M , Zhang T , Lei G , Zhuang Y and Mao X 2024 Popeye: a unified visual-language model for multi-source ship detection from remote sensing imagery IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 17 20050 – 63

Pei D , He J , Liu K , Chen M and Zhang S 2024 Application of large language models and assessment of their ship-handling theory knowledge and skills for connected maritime autonomous surface ships Mathematics 12 2381

Kim T-Y and Choi W-S 2025 Autonomous vehicle maneuvering using vision–LLM models for marine surface vehicles J. Mar. Sci. Eng. 13 1553

Hu X , Zhang J , Liu W and Ma Z 2025 As-LLM: an LLM-based framework for industrial autonomous system relationship inference 2025 Joint Int. Conf. on Automation-Intelligence-Safety (ICAIS) & Int. Symp. on Autonomous Systems (ISAS) ( IEEE ) pp 1 – 6

Ren Y , Zhang H , Richard Yu F , Li W , Zhao P and He. Y 2024 Industrial internet of things with large language models (LLMS): an intelligence-based reinforcement learning approach IEEE Trans. Mobile Comput. 24 4136 – 52

Wang Y , Jiao R , Lang C , Zhan S S , Huang C , Wang Z , Yang Z and Zhu Q 2023 Empowering autonomous driving with large language models: a safety perspective (arXiv:2312.00812)

Sobrín-Hidalgo D , González-Santamarta M A , Guerrero-Higueras Angel M , Rodríguez-Lera F J and Matellán-Olivera V 2024 Explaining autonomy: enhancing human-robot interaction through explanation generation with large language models (arXiv:2402.04206)

Buchmann R , Eder J , Fill H-G , Frank U , Karagiannis D , Laurenzi E , Mylopoulos J , Plexousakis D and Santos M Y 2024 Large language models: expectations for semantics-driven systems engineering Data Knowl. Eng. 152 102324

Zaki O , Dunnigan M , Robu V and Flynn D 2021 Reliability and safety of autonomous systems based on semantic modelling for self-certification Robotics 10 10

Lyons J B , Clark M A , Wagner A R and Schuelke M J 2017 Certifiable trust in autonomous systems: making the intractable tangible AI Mag. 38 37 – 49

Vaid A et al 2024 Generative large language models are autonomous practitioners of evidence-based medicine (arXiv:2401.02851)

Tao Z , Lin T-E , Chen X , Li H , Wu Y , Li Y , Jin Z , Huang F , Tao D and Zhou J 2024 A survey on self-evolution of large language models (arXiv:2404.14387)

Popescu N 2022 Safety verification and validation techniques for autonomous driving systems J. Human. Appl. Sci. Res. 5 71 – 87

Zheng Xi , Mok A K , Piskac R , Lee Y J , Krishnamachari B , Zhu D , Sokolsky O and Lee I 2024 Testing learning-enabled cyber-physical systems with large-language models: a formal approach Companion Proc. 32nd ACM Int. Conf. on the Foundations of Software Engineering pp 467 – 71

Kong X , Braunl T , Fahmi M and Wang Y 2024 A superalignment framework in autonomous driving with large language models (arXiv:2406.05651)

Wu T , He S , Liu J , Sun S , Liu K , Han Q-L and Tang Y 2023 A brief overview of ChatGPT: the history, status quo and potential future development IEEE/CAA J. Autom. Sinica 10 1122 – 36

Wang L et al 2024 A survey on large language model based autonomous agents Front. Comput. Sci. 18 186345

Mann S P , Jiehao J S , Latham S R , Savulescu J , Aboy M and Earp B D 2025 Development of application-specific large language models to facilitate research ethics review (arXiv:2501.10741)

Corfmat M , Martineau J T and Régis C 2025 High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare BMC Med. Ethics 26 4

Acharya K , Velasquez A and Song H H 2024 A survey on symbolic knowledge distillation of large language models IEEE Trans. Artif. Intell. 5 5928 – 48

Van Noorden R 2023 ChatGPT-like AIS are coming to major science searches Nature 620 258

Lu Y , Tian Y , Bi Y , Chen B and Peng X 2024 Diavio: LLM-empowered diagnosis of safety violations in ads simulation testing Proc. 33rd ACM SIGSOFT Int. Symp. on Software Testing and Analysis pp 376 – 88

Jha C K et al 2025 Large language models (LLMs) for verification, testing and design 2025 IEEE European Test Symp. (ETS) ( IEEE ) pp 1 – 10

Lu Q , Wang X , Jiang Y , Zhao G , Ma M and Feng S 2025 Omnitester: multimodal large language model driven scenario testing for autonomous vehicles Autom. Innov. 8 1 – 15

Zhou Y , Cui C , Peng J , Yang Z , Lu J , Panchal J , Yao B and Wang Z 2025 A hierarchical test platform for vision language model (VLM)-integrated real-world autonomous driving ACM Trans. Internet Things ( https://doi.org/10.1145/3769867 https://doi.org/10.1145/3769867 )

Esposito M , Palagiano F , Lenarduzzi V and Taibi D 2025 On large language models in mission-critical it governance: are we ready yet? 2025 IEEE/ACM 47th Int. Conf. on Software Engineering: Software Engineering in Practice (ICSE-SEIP) ( IEEE ) pp 504 – 15