{"id":"https://openalex.org/W4412825678","doi":"https://doi.org/10.1145/3711896.3736878","title":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","display_name":"CityGPT: Empowering Urban Spatial Cognition of Large Language Models","publication_year":2025,"publication_date":"2025-08-01","ids":{"openalex":"https://openalex.org/W4412825678","doi":"https://doi.org/10.1145/3711896.3736878"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3736878","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736878","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3711896.3736878","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100668035","display_name":"Jie Feng","orcid":"https://orcid.org/0000-0003-3279-7117"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Feng","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3279-7117","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069964817","display_name":"T. Liu","orcid":"https://orcid.org/0009-0005-9729-9700"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianhui Liu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-9729-9700","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069959549","display_name":"Yangzhou Du","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Du","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-7197-4367","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101384209","display_name":"Siqi Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Guo","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-0837-7498","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032748650","display_name":"Yuming Lin","orcid":"https://orcid.org/0000-0003-0442-7071"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Lin","raw_affiliation_strings":["Department of Urban Planning, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0442-7071","affiliations":[{"raw_affiliation_string":"Department of Urban Planning, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5617-1659","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100668035"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":12.9826,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.98659989,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"591","last_page":"602"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7281665205955505},{"id":"https://openalex.org/keywords/spatial-cognition","display_name":"Spatial cognition","score":0.685858428478241},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.6227725744247437},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32086536288261414},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12544509768486023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281665205955505},{"id":"https://openalex.org/C2777371692","wikidata":"https://www.wikidata.org/wiki/Q2178611","display_name":"Spatial cognition","level":3,"score":0.685858428478241},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.6227725744247437},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32086536288261414},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12544509768486023},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3736878","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736878","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3736878","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736878","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2153207204","https://openalex.org/W2898502679","https://openalex.org/W4220700859","https://openalex.org/W4221159132","https://openalex.org/W4224266081","https://openalex.org/W4226244192","https://openalex.org/W4309646944","https://openalex.org/W4328127395","https://openalex.org/W4385572793","https://openalex.org/W4387321091","https://openalex.org/W4389519291","https://openalex.org/W4390100400","https://openalex.org/W4392384758","https://openalex.org/W4411119500","https://openalex.org/W4411735734","https://openalex.org/W6840334356","https://openalex.org/W6890025973"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2383422963","https://openalex.org/W4214938495","https://openalex.org/W2890636435","https://openalex.org/W2373106690","https://openalex.org/W2009009025"],"abstract_inverted_index":{"Large":[0],"language":[1,6],"models(LLMs),":[2],"with":[3,196],"their":[4,72,107,143,152,233],"powerful":[5],"generation":[7],"and":[8,21,47,70,104,116,126,139,185,208,237,247,252],"reasoning":[9,109],"capabilities,":[10],"have":[11],"already":[12],"achieved":[13],"notable":[14],"success":[15],"in":[16,209],"many":[17],"domains,":[18],"e.g.,":[19],"math":[20],"code":[22,249],"generation.":[23],"However,":[24],"they":[25],"often":[26],"fall":[27],"short":[28],"when":[29,216],"tackling":[30],"real-life":[31],"geospatial":[32,186],"tasks":[33,79],"within":[34],"urban":[35,68,78,100,144,183],"environments.":[36,243],"This":[37],"limitation":[38],"stems":[39],"from":[40],"a":[41,59,82,92,112,124,166,179],"lack":[42],"of":[43,67,114,160,176,182],"physical":[44,242],"world":[45],"knowledge":[46,101,228],"relevant":[48],"data":[49],"during":[50],"training.":[51],"To":[52],"address":[53],"this":[54],"gap,":[55],"we":[56,90,122,164],"propose":[57],"CityGPT,":[58],"systematic":[60],"framework":[61],"designed":[62],"to":[63,74,132,141,156,239],"enhance":[64,142],"LLMs'":[65],"understanding":[66],"space":[69],"improve":[71],"ability":[73],"solve":[75],"the":[76,87,158,174,223,240],"related":[77],"by":[80,198],"integrating":[81,226],"city-scale":[83],"'world":[84],"model'":[85],"into":[86,102,229],"model.":[88],"Firstly,":[89],"construct":[91],"diverse":[93],"instruction":[94,120],"tuning":[95],"dataset,":[96,245],"CityInstruction,":[97],"for":[98,172,225],"injecting":[99],"LLMs":[103,135,177,194,215],"effectively":[105],"boosting":[106],"spatial":[108,145,169,227,234],"capabilities.":[110],"Using":[111],"combination":[113],"CityInstruction":[115,197],"open":[117],"source":[118,248],"general":[119,153],"data,":[121],"introduce":[123],"novel":[125],"easy-to-use":[127],"self-weighted":[128],"fine-tuning":[129],"method":[130,200],"(SWFT)":[131],"train":[133],"various":[134],"(including":[136],"ChatGLM3-6B,":[137],"Llama3-8B,":[138],"Qwen2.5-7B)":[140],"capabilities":[146],"without":[147],"compromising,":[148],"or":[149],"even":[150],"improving,":[151],"abilities.":[154],"Finally,":[155],"validate":[157],"effectiveness":[159],"our":[161],"proposed":[162],"framework,":[163],"develop":[165],"comprehensive":[167],"text-based":[168],"benchmark":[170],"CityEval":[171],"evaluating":[173],"performance":[175,203],"across":[178],"wide":[180],"range":[181],"scenarios":[184],"tasks.":[187],"Extensive":[188],"evaluation":[189],"results":[190],"demonstrate":[191],"that":[192,204],"smaller":[193],"trained":[195],"SWFT":[199],"can":[201,253],"achieve":[202],"is":[205],"competitive":[206],"with,":[207],"some":[210],"cases":[211],"superior":[212],"to,":[213],"proprietary":[214],"assessed":[217],"using":[218],"CityEval.":[219],"Our":[220],"work":[221],"highlights":[222],"potential":[224],"LLMs,":[230],"thereby":[231],"expanding":[232],"cognition":[235],"abilities":[236],"applicability":[238],"real-world":[241],"The":[244],"benchmark,":[246],"are":[250],"open-sourced":[251],"be":[254],"accessed":[255],"through":[256],"https://github.com/tsinghua-fib-lab/CityGPT.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
