{"id":"https://openalex.org/W7138921422","doi":"https://doi.org/10.1609/aaai.v40i45.41232","title":"LSDTs: LLM-Augmented Semantic Digital Twins for Adaptive Knowledge-Intensive Infrastructure Planning","display_name":"LSDTs: LLM-Augmented Semantic Digital Twins for Adaptive Knowledge-Intensive Infrastructure Planning","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138921422","doi":"https://doi.org/10.1609/aaai.v40i45.41232"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i45.41232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i45.41232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/41232/45193","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/41232/45193","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054121207","display_name":"Naiyi Li","orcid":"https://orcid.org/0000-0002-3398-0418"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naiyi Li","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036241480","display_name":"Zihui Ma","orcid":"https://orcid.org/0000-0002-2836-280X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zihui Ma","raw_affiliation_strings":["University of Maryland, College Park\nNew York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park\nNew York University","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767610","display_name":"Runlong Yu","orcid":"https://orcid.org/0000-0003-4080-2377"},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Runlong Yu","raw_affiliation_strings":["University of Alabama"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alabama","institution_ids":["https://openalex.org/I17301866"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031522503","display_name":"Lingyao Li","orcid":"https://orcid.org/0000-0001-5888-8311"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingyao Li","raw_affiliation_strings":["University of South Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Florida","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40361446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"45","first_page":"38871","last_page":"38879"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11006","display_name":"BIM and Construction Integration","score":0.2551000118255615,"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"}},"topics":[{"id":"https://openalex.org/T11006","display_name":"BIM and Construction Integration","score":0.2551000118255615,"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/T10763","display_name":"Digital Transformation in Industry","score":0.08820000290870667,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11479","display_name":"Smart Cities and Technologies","score":0.04610000178217888,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/ontology","display_name":"Ontology","score":0.6478000283241272},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5674999952316284},{"id":"https://openalex.org/keywords/chatbot","display_name":"Chatbot","score":0.45239999890327454},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.41290000081062317},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4074999988079071},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.3492000102996826},{"id":"https://openalex.org/keywords/scenario-planning","display_name":"Scenario planning","score":0.3328999876976013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049000263214111},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.6478000283241272},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5674999952316284},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40220001339912415},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C202033279","wikidata":"https://www.wikidata.org/wiki/Q1931373","display_name":"Scenario planning","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C101230327","wikidata":"https://www.wikidata.org/wiki/Q826165","display_name":"Web Ontology Language","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.30070000886917114},{"id":"https://openalex.org/C6881194","wikidata":"https://www.wikidata.org/wiki/Q7449091","display_name":"Semantic technology","level":4,"score":0.2750999927520752},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.25760000944137573},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C102993220","wikidata":"https://www.wikidata.org/wiki/Q387196","display_name":"Description logic","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25060001015663147},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i45.41232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i45.41232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/41232/45193","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i45.41232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i45.41232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/41232/45193","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5960280895233154,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138921422.pdf","grobid_xml":"https://content.openalex.org/works/W7138921422.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Digital":[0,53],"Twins":[1],"(DTs)":[2],"offer":[3],"powerful":[4],"tools":[5],"for":[6],"managing":[7],"complex":[8],"infrastructure":[9,139],"systems,":[10],"but":[11],"their":[12],"effectiveness":[13],"is":[14],"often":[15],"limited":[16],"by":[17],"challenges":[18],"in":[19,25,40,115,138],"integrating":[20],"unstructured":[21,64],"knowledge.":[22],"Recent":[23],"advances":[24],"Large":[26],"Language":[27],"Models":[28],"(LLMs)":[29],"bring":[30],"new":[31],"potential":[32,145],"to":[33,97,153],"address":[34],"this":[35],"gap,":[36],"with":[37,150],"strong":[38],"abilities":[39],"extracting":[41],"and":[42,69,72,135],"organizing":[43],"diverse":[44],"textual":[45],"information.":[46],"We":[47,103],"therefore":[48],"propose":[49],"LSDTs":[50,105,126],"(LLM-Augmented":[51],"Semantic":[52],"Twins),":[54],"a":[55,76,82,87,107],"framework":[56],"that":[57,85,125],"helps":[58],"LLMs":[59],"extract":[60],"planning":[61,101,114,157],"knowledge":[62],"from":[63],"documents":[65],"like":[66],"environmental":[67],"regulations":[68],"technical":[70],"guidelines,":[71],"organize":[73],"it":[74,96],"into":[75],"formal":[77],"ontology.":[78],"This":[79,141],"ontology":[80],"forms":[81],"semantic":[83],"layer":[84],"powers":[86],"digital":[88,151],"twin\u2014a":[89],"virtual":[90],"model":[91],"of":[92,110,146],"the":[93,144],"physical":[94],"system\u2014allowing":[95],"simulate":[98],"realistic,":[99],"regulation-aware":[100,129],"scenarios.":[102],"evaluate":[104],"through":[106],"case":[108],"study":[109],"offshore":[111],"wind":[112],"farm":[113],"Maryland,":[116],"including":[117],"its":[118],"application":[119],"during":[120],"Hurricane":[121],"Sandy.":[122],"Results":[123],"demonstrate":[124],"support":[127,154],"interpretable,":[128],"layout":[130],"optimization,":[131],"enable":[132],"high-fidelity":[133],"simulation,":[134],"enhance":[136],"adaptability":[137],"planning.":[140],"work":[142],"shows":[143],"combining":[147],"generative":[148],"AI":[149],"twins":[152],"complex,":[155],"knowledge-driven":[156],"tasks.":[158]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-20T00:00:00"}