{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T16:27:03Z","timestamp":1783614423632,"version":"3.55.0"},"reference-count":172,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62302527"],"award-info":[{"award-number":["62302527"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020226","name":"Hunan Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2023jj40774"],"award-info":[{"award-number":["2023jj40774"]}],"id":[{"id":"10.13039\/501100020226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"High Performance Computing Center of Central South University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Commun. Surv. Tutorials"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/comst.2025.3568637","type":"journal-article","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T14:03:48Z","timestamp":1746799428000},"page":"3388-3411","source":"Crossref","is-referenced-by-count":38,"title":["A Survey on Applications of Large Language Model-Driven Digital Twins for Intelligent Network Optimization"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2209-8216","authenticated-orcid":false,"given":"Zhiqi","family":"Guo","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2414-4802","authenticated-orcid":false,"given":"Fengxiao","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9518-2527","authenticated-orcid":false,"given":"Linfeng","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2317-5359","authenticated-orcid":false,"given":"Ming","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8769-302X","authenticated-orcid":false,"given":"Nei","family":"Kato","sequence":"additional","affiliation":[{"name":"Graduate School of Information Sciences, Tohoku University, Sendai, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2023.3249835"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2024.3390543"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3369250"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3422613"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2019.2921208"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3136860"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/9614520"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3103320"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3047613"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.icte.2022.06.006"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3429341"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.001.1900333"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2957648"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2021.3071496"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.001.2100338"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2023.3244674"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/EuCNC\/6GSummit51104.2021.9482503"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-022-01937-3"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3098632"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3061697"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2021.3130901"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-021-01790-w"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2024.3437365"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.33050\/italic.v2i2.530"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10311-023-01591-5"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2024.3420120"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.2200854"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2020.3019650"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-69474-5"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3624724"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW63382.2024.00724"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3624918.3629548"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-44693-1_30"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-45563-x"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681488"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2873186"},{"key":"ref37","article-title":"Digital twin aided adversarial transfer learning method for domain adaptation fault diagnosis","volume":"234","author":"Wang","year":"2023","journal-title":"Rel. Eng. System Saf."},{"key":"ref38","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2023.102682","article-title":"Multi-objective coupling optimization of electrical cable intelligent production line driven by digital twin","volume":"86","author":"Yuan","year":"2024","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref39","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109099","article-title":"Reference architecture for digital twin-based predictive maintenance systems","volume":"177","author":"van Dinter","year":"2023","journal-title":"Comput. Ind. Eng."},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2024.3393503"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3079510"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCA62789.2024.10591881"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2024.3435752"},{"key":"ref44","article-title":"Large language model (LLM) for telecommunications: A comprehensive survey on principles, key techniques, and opportunities","author":"Zhou","year":"2024","journal-title":"arXiv:2405.10825"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.2300550"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3651890.3672268"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ELECOM54934.2022.9965265"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2022.3198273"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICECET61485.2024.10698138"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.21143"},{"key":"ref51","article-title":"A survey of large language models","author":"Zhao","year":"2023","journal-title":"arXiv:2303.18223"},{"key":"ref52","volume-title":"Statistical Methods for Speech Recognition","author":"Jelinek","year":"1998"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/5.880083"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.21236\/ADA440321"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2010-343"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2012-65"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ASRU.2013.6707742"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-22482-4_11"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"ref60","article-title":"On using very large target vocabulary for neural machine translation","author":"Jean","year":"2014","journal-title":"arXiv:1412.2007"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref62","first-page":"2","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. NAACL-HLT","volume":"1","author":"Kenton"},{"key":"ref63","article-title":"Improving language understanding by generative pretraining.","author":"Radford","year":"2018"},{"key":"ref64","article-title":"Language models are few-shot learners","author":"Brown","year":"2020","journal-title":"arXiv:2005.14165"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-020-09548-1"},{"key":"ref66","article-title":"GPT-4 technical report","volume-title":"arXiv:2303.08774","author":"Achiam","year":"2023"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i3.27999"},{"key":"ref68","first-page":"2629","article-title":"Generating images with multimodal language models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Koh"},{"key":"ref69","article-title":"DeepSeek-R1: Incentivizing reasoning capability in LLMS via reinforcement learning","author":"Guo","year":"2025","journal-title":"arXiv:2501.12948"},{"key":"ref70","first-page":"22964","article-title":"What language model architecture and pretraining objective works best for zero-shot generalization?","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Wang"},{"issue":"70","key":"ref71","first-page":"1","article-title":"Scaling instruction-finetuned language models","volume":"25","author":"Chung","year":"2024","journal-title":"J. Mach. Learn. Res."},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.782"},{"key":"ref73","article-title":"Prompt engineering guide.","author":"Saravia","year":"2022"},{"key":"ref74","first-page":"1","article-title":"Tree of thoughts: Deliberate problem solving with large language models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Yao"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73397-0_18"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i21.30570"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01311"},{"key":"ref78","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref79","article-title":"Decoupled weight decay regularization","author":"Loshchilov","year":"2017","journal-title":"arXiv:1711.05101"},{"key":"ref80","article-title":"Bloom: A 176b-parameter open-access multilingual language model.","author":"Scao","year":"2023"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS60453.2023.00126"},{"key":"ref82","article-title":"Basis sharing: Cross-layer parameter sharing for large language model compression","author":"Wang","year":"2024","journal-title":"arXiv:2410.03765"},{"issue":"1","key":"ref83","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref84","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Wen"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21408"},{"key":"ref86","first-page":"38087","article-title":"SmoothQuant: Accurate and efficient post-training quantization for large language models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xiao"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i12.29237"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref89","first-page":"14852","article-title":"Large language models are reasoning teachers","volume-title":"Proc. 61st Annu. Meeting Assoc. Comput. Linguist.","author":"Ho"},{"key":"ref90","first-page":"10421","article-title":"Specializing smaller language models towards multi-step reasoning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Fu"},{"key":"ref91","first-page":"20852","article-title":"Less is more: Task-aware layer-wise distillation for language model compression","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liang"},{"key":"ref92","first-page":"6","article-title":"MiniLLM: Knowledge distillation of large language models","volume-title":"Proc. 12th Int. Conf. Learn. Rep.","author":"Gu"},{"key":"ref93","first-page":"720","article-title":"Weighted low-rank approximations","volume-title":"Proc. 20th Int. Conf. Mach. Learn. (ICML)","author":"Srebro"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.372"},{"key":"ref95","article-title":"DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter","author":"Sanh","year":"2019","journal-title":"arXiv:1910.01108"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.195"},{"key":"ref97","article-title":"Albert: A lite bert for self-supervised learning of language representations","author":"Lan","year":"2019","journal-title":"arXiv:1909.11942"},{"key":"ref98","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014","journal-title":"arXiv:1412.6572"},{"key":"ref99","article-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2017","journal-title":"arXiv:1706.06083"},{"key":"ref100","first-page":"1","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Lundberg"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3020"},{"key":"ref102","first-page":"24824","article-title":"Chain-of-thought prompting elicits reasoning in large language models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Wei"},{"key":"ref103","article-title":"Automatic chain of thought prompting in large language models","author":"Zhang","year":"2022","journal-title":"arXiv:2210.03493"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1504\/IJPD.2005.006669"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.2514\/6.2012-1818"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2022.3208773"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1007\/s40436-020-00302-5"},{"issue":"1","key":"ref108","first-page":"1","article-title":"Digitalization transformation of power transmission and transformation under the background of new power system","volume":"48","author":"Jiang","year":"2022","journal-title":"High Voltage Eng."},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-18732-3"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2022.101858"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2020.102412"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2022.10.004"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1016\/j.engfracmech.2020.107076"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3051158"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00610-z"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1016\/j.ref.2023.100530"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1093\/ce\/zkz025"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2023.100443"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2023.2217291"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.014.2200371"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2022.3179207"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2021.103586"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2020.110208"},{"issue":"1","key":"ref124","first-page":"8","article-title":"Applying digital twins in metaverse: User interface, security and privacy challenges","volume":"2","author":"Far","year":"2022","journal-title":"J. Metaverse"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1007\/s00158-022-03425-4"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2019.05.020"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2021.107938"},{"key":"ref128","first-page":"334","article-title":"Data validation for machine learning","volume-title":"Proc. Mach. Learn. Syst.","volume":"1","author":"Polyzotis"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2017.1394596"},{"key":"ref130","doi-asserted-by":"publisher","DOI":"10.1063\/1.5031520"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2018.03.178"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2019.106612"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2023.100469"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2016.2590997"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.1109\/ICNSC.2018.8361272"},{"key":"ref136","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2018.1552032"},{"key":"ref137","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.117899"},{"key":"ref138","doi-asserted-by":"publisher","DOI":"10.1080\/0951192X.2021.1992666"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1093\/jcde\/qwac032"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2020.04.012"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-019-01500-0"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1109\/ICPRE51194.2020.9233278"},{"key":"ref143","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-019-01516-6"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2019.01.014"},{"key":"ref145","doi-asserted-by":"publisher","DOI":"10.1038\/s43588-024-00603-w"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3045123"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1145\/3583740.3626806"},{"key":"ref148","doi-asserted-by":"publisher","DOI":"10.1109\/MIPRO60963.2024.10569919"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1109\/MobiSecServ58080.2023.10329224"},{"key":"ref150","article-title":"LLM experiments with simulation: Large language model multi-agent system for process simulation Parametrization in digital twins","author":"Xia","year":"2024","journal-title":"arXiv:2405.18092"},{"key":"ref151","doi-asserted-by":"publisher","DOI":"10.3390\/s23229225"},{"key":"ref152","article-title":"TPLLM: A traffic prediction framework based on pretrained large language models","author":"Ren","year":"2024","journal-title":"arXiv:2403.02221"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2024.110382"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3519576"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1145\/3600100.3623719"},{"key":"ref156","article-title":"DefectTwin: When LLM meets digital twin for railway defect inspection","author":"Ferdousi","year":"2024","journal-title":"arXiv:2409.06725"},{"key":"ref157","doi-asserted-by":"publisher","DOI":"10.1109\/QRS-C63300.2024.00021"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1016\/j.icte.2024.07.007"},{"key":"ref159","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3415470"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2022.3197811"},{"key":"ref161","article-title":"Self-refined generative foundation models for wireless traffic prediction.","author":"Hu","year":"2024"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2024.3421306"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/mnet.2024.3511662"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/VTC2024-Fall63153.2024.10757470"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1109\/6GNet58894.2023.10317780"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.23919\/JCIN.2023.10272352"},{"key":"ref167","article-title":"6G comprehensive intelligence: Network operations and optimization based on large language models","author":"Long","year":"2024","journal-title":"arXiv:2404.18373"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1109\/mcom.001.2400368"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.005.2400019"},{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1007\/s44212-024-00060-w"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2024.02.015"},{"key":"ref172","first-page":"9","article-title":"Large language models are zero-shot time series forecasters","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Gruver"}],"container-title":["IEEE Communications Surveys &amp; Tutorials"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/9739\/11321210\/10994494.pdf?arnumber=10994494","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T05:42:56Z","timestamp":1767332576000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10994494\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":172,"URL":"https:\/\/doi.org\/10.1109\/comst.2025.3568637","relation":{},"ISSN":["1553-877X","2373-745X"],"issn-type":[{"value":"1553-877X","type":"electronic"},{"value":"2373-745X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}