{"id":"https://openalex.org/W7138892867","doi":"https://doi.org/10.1109/globecom59602.2025.11431973","title":"Open-Source LLM-Driven Federated Transformer for Predictive IoV Management","display_name":"Open-Source LLM-Driven Federated Transformer for Predictive IoV Management","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138892867","doi":"https://doi.org/10.1109/globecom59602.2025.11431973"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11431973","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431973","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.00651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014662198","display_name":"Yazan Otoum","orcid":"https://orcid.org/0000-0002-5500-3060"},"institutions":[{"id":"https://openalex.org/I86519414","display_name":"Algoma University","ror":"https://ror.org/0131d6623","country_code":"CA","type":"education","lineage":["https://openalex.org/I86519414"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yazan Otoum","raw_affiliation_strings":["Algoma University,School of Computer Science and Technology,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Algoma University,School of Computer Science and Technology,Canada","institution_ids":["https://openalex.org/I86519414"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041995126","display_name":"Arghavan Asad","orcid":"https://orcid.org/0000-0001-9254-9479"},"institutions":[{"id":"https://openalex.org/I86519414","display_name":"Algoma University","ror":"https://ror.org/0131d6623","country_code":"CA","type":"education","lineage":["https://openalex.org/I86519414"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Arghavan Asad","raw_affiliation_strings":["Algoma University,School of Computer Science and Technology,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Algoma University,School of Computer Science and Technology,Canada","institution_ids":["https://openalex.org/I86519414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055456145","display_name":"Ishtiaq Ahmad","orcid":"https://orcid.org/0000-0001-6856-7466"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Ishtiaq Ahmad","raw_affiliation_strings":["Czech Technical University in Prague,Faculty of Electrical Engineering,Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Czech Technical University in Prague,Faculty of Electrical Engineering,Czech Republic","institution_ids":["https://openalex.org/I44504214"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1859","last_page":"1864"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.49219998717308044,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.49219998717308044,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.21150000393390656,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.03269999846816063,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.571399986743927},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5529999732971191},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5115000009536743},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.44780001044273376},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.4108999967575073},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.3176000118255615},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.30000001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645999789237976},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.571399986743927},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5115000009536743},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3192000091075897},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26030001044273376}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/globecom59602.2025.11431973","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431973","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2505.00651","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.00651","pdf_url":"https://arxiv.org/pdf/2505.00651","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2505.00651","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.00651","pdf_url":"https://arxiv.org/pdf/2505.00651","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138892867.pdf","grobid_xml":"https://content.openalex.org/works/W7138892867.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2137693329","https://openalex.org/W4297990046","https://openalex.org/W4391547738","https://openalex.org/W4396214366","https://openalex.org/W4400257644","https://openalex.org/W4404103221","https://openalex.org/W4406266464","https://openalex.org/W4407155130","https://openalex.org/W4407391761","https://openalex.org/W4408324949","https://openalex.org/W4408926690"],"related_works":[],"abstract_inverted_index":{"The":[0,116],"proliferation":[1],"of":[2,8,68,187],"connected":[3],"vehicles":[4],"within":[5],"the":[6,83,154,185],"Internet":[7],"Vehicles":[9],"(IoV)":[10],"ecosystem":[11],"presents":[12],"critical":[13],"challenges":[14],"in":[15,49,60,66,74,153,190,205],"ensuring":[16],"scalable,":[17],"real-time,":[18],"and":[19,34,51,71,194],"privacy-preserving":[20],"traffic":[21,151],"management.":[22,99],"Existing":[23],"centralized":[24],"IoV":[25,98,196],"solutions":[26,204],"often":[27],"suffer":[28],"from":[29],"high":[30,177],"latency,":[31],"limited":[32],"scalability,":[33],"reliance":[35],"on":[36,172,179],"proprietary":[37,203],"Artificial":[38],"Intelligence":[39],"(AI)":[40],"models,":[41],"creating":[42],"significant":[43],"barriers":[44],"to":[45,112,134,145,202],"widespread":[46],"deployment,":[47],"particularly":[48,65],"dynamic":[50,103],"privacy-sensitive":[52],"environments.":[53],"Meanwhile,":[54],"integrating":[55],"Large":[56],"Language":[57],"Models":[58],"(LLMs)":[59],"vehicular":[61],"systems":[62],"remains":[63],"underexplored,":[64],"terms":[67],"prompt":[69,104],"optimization":[70,105],"effective":[72],"utilization":[73],"federated":[75,121],"contexts.":[76],"To":[77],"address":[78],"these":[79],"challenges,":[80],"we":[81],"propose":[82],"Federated":[84],"Prompt-Optimized":[85],"Traffic":[86],"Transformer":[87],"(FPoTT),":[88],"a":[89,102,119,199],"novel":[90],"framework":[91],"that":[92,107,163],"leverages":[93],"open-source":[94,188],"LLMs":[95,133,189],"for":[96,128],"predictive":[97],"FPoTT":[100],"introduces":[101],"mechanism":[106],"iteratively":[108],"refines":[109],"textual":[110],"prompts":[111],"enhance":[113],"trajectory":[114],"prediction.":[115],"architecture":[117],"employs":[118],"dual-layer":[120],"learning":[122],"paradigm,":[123],"combining":[124],"lightweight":[125],"edge":[126],"models":[127],"real-time":[129],"inference":[130],"with":[131,148],"cloud-based":[132],"retain":[135],"global":[136],"intelligence.":[137],"A":[138],"Transformer-driven":[139],"synthetic":[140,180],"data":[141,174],"generator":[142],"is":[143],"incorporated":[144],"augment":[146],"training":[147],"diverse,":[149],"high-fidelity":[150],"scenarios":[152],"Next":[155],"Generation":[156],"Simulation":[157],"(NGSIM)":[158],"format.":[159],"Extensive":[160],"evaluations":[161],"demonstrate":[162],"FPoTT,":[164],"utilizing":[165],"EleutherAI":[166],"Pythia-1B,":[167],"achieves":[168],"99.86%":[169],"prediction":[170],"accuracy":[171],"real-world":[173],"while":[175],"maintaining":[176],"performance":[178],"datasets.":[181],"These":[182],"results":[183],"highlight":[184],"potential":[186],"facilitating":[191],"secure,":[192],"adaptive,":[193],"scalable":[195],"management,":[197],"providing":[198],"promising":[200],"alternative":[201],"smart":[206],"mobility":[207],"ecosystems.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2026-03-20T00:00:00"}