{"id":"https://openalex.org/W4415697196","doi":"https://doi.org/10.1145/3764915.3770723","title":"HiCoTraj: Zero-Shot Demographic Reasoning via Hierarchical Chain-of-Thought Prompting from Trajectory","display_name":"HiCoTraj: Zero-Shot Demographic Reasoning via Hierarchical Chain-of-Thought Prompting from Trajectory","publication_year":2025,"publication_date":"2025-10-30","ids":{"openalex":"https://openalex.org/W4415697196","doi":"https://doi.org/10.1145/3764915.3770723"},"language":"en","primary_location":{"id":"doi:10.1145/3764915.3770723","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3764915.3770723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Generative and Agentic AI for Multi-Modality Space-Time Intelligence","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/2510.12067","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Junyi Xie","orcid":"https://orcid.org/0009-0006-6936-3987"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junyi Xie","raw_affiliation_strings":["University of Minnesota, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0009-0006-6936-3987","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009881593","display_name":"Yuankun Jiao","orcid":"https://orcid.org/0000-0002-4188-5066"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuankun Jiao","raw_affiliation_strings":["University of Minnesota, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0000-0002-4188-5066","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646674","display_name":"Jina Kim","orcid":"https://orcid.org/0000-0003-1140-6113"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jina Kim","raw_affiliation_strings":["University of Minnesota, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0000-0003-1140-6113","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045786247","display_name":"Yao\u2010Yi Chiang","orcid":"https://orcid.org/0000-0002-8923-0130"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao-Yi Chiang","raw_affiliation_strings":["University of Minnesota, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0000-0002-8923-0130","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074800190","display_name":"Lingyi Zhao","orcid":"https://orcid.org/0000-0001-8544-3326"},"institutions":[{"id":"https://openalex.org/I4210151176","display_name":"Novateur Research Solutions (United States)","ror":"https://ror.org/04gc7ef93","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151176"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingyi Zhao","raw_affiliation_strings":["Novateur Research Solutions, Ashburn, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0001-8544-3326","affiliations":[{"raw_affiliation_string":"Novateur Research Solutions, Ashburn, Virginia, USA","institution_ids":["https://openalex.org/I4210151176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083630319","display_name":"Khurram Shafique","orcid":"https://orcid.org/0000-0002-3834-324X"},"institutions":[{"id":"https://openalex.org/I4210151176","display_name":"Novateur Research Solutions (United States)","ror":"https://ror.org/04gc7ef93","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151176"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khurram Shafique","raw_affiliation_strings":["Novateur Research Solutions, Ashburn, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0002-3834-324X","affiliations":[{"raw_affiliation_string":"Novateur Research Solutions, Ashburn, Virginia, USA","institution_ids":["https://openalex.org/I4210151176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.36343284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"49","last_page":"53"},"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":0.6940000057220459,"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":0.6940000057220459,"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/T11106","display_name":"Data Management and Algorithms","score":0.03700000047683716,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.031099999323487282,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.859499990940094},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7232000231742859},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6219000220298767},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5286999940872192},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42989999055862427},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.3774999976158142}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.859499990940094},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7232000231742859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6610999703407288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6266999840736389},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6219000220298767},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5286999940872192},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.521399974822998},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.3774999976158142},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.275299996137619},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.26440000534057617}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3764915.3770723","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3764915.3770723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Generative and Agentic AI for Multi-Modality Space-Time Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2510.12067","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.12067","pdf_url":"https://arxiv.org/pdf/2510.12067","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:2510.12067","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.12067","pdf_url":"https://arxiv.org/pdf/2510.12067","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"id":"https://openalex.org/G1894767750","display_name":null,"funder_award_id":"140D0423C0033","funder_id":"https://openalex.org/F4320333051","funder_display_name":"Intelligence Advanced Research Projects Activity"}],"funders":[{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333452","display_name":"Interior Business Center","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415697196.pdf","grobid_xml":"https://content.openalex.org/works/W4415697196.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W2293286118","https://openalex.org/W2966664041","https://openalex.org/W4382938621","https://openalex.org/W4390086733","https://openalex.org/W4407922851"],"related_works":[],"abstract_inverted_index":{"Inferring":[0],"demographic":[1,32,42,82,131,144,165],"attributes":[2,166],"such":[3,17],"as":[4,18],"age,":[5],"sex,":[6],"or":[7],"income":[8],"level":[9],"from":[10,67],"human":[11],"mobility":[12],"patterns":[13],"enables":[14],"critical":[15],"applications":[16],"targeted":[19],"public":[20],"health":[21],"interventions,":[22],"equitable":[23],"urban":[24],"planning,":[25],"and":[26,48,54,76,102,130],"personalized":[27],"transportation":[28],"services.":[29],"Existing":[30],"mobility-based":[31],"inference":[33,83,132],"studies":[34],"heavily":[35],"rely":[36],"on":[37,153],"large-scale":[38],"trajectory":[39,155],"data":[40,145,156],"with":[41,133],"labels,":[43],"leading":[44],"to":[45,80,116],"limited":[46],"interpretability":[47],"poor":[49],"generalizability":[50],"across":[51,163],"different":[52],"datasets":[53],"user":[55],"groups.":[56],"We":[57],"propose":[58],"HiCoTraj":[59,88,107,159],"(Zero-Shot":[60],"Demographic":[61],"Reasoning":[62],"via":[63],"Hierarchical":[64],"Chain-of-Thought":[65],"Prompting":[66],"Trajectory),":[68],"a":[69,109],"framework":[70],"that":[71,158],"leverages":[72],"LLMs'":[73],"zero-shot":[74,168],"learning":[75],"semantic":[77],"understanding":[78],"capabilities":[79],"perform":[81],"without":[84],"labeled":[85,143],"training":[86],"data.":[87],"transforms":[89],"trajectories":[90],"into":[91],"semantically":[92],"rich,":[93],"natural":[94],"language":[95],"representations":[96],"by":[97],"creating":[98],"detailed":[99],"activity":[100],"chronicles":[101],"multi-scale":[103],"visiting":[104],"summaries.":[105],"Then":[106],"uses":[108],"novel":[110],"hierarchical":[111],"chain":[112],"of":[113,142],"thought":[114],"reasoning":[115,149],"systematically":[117],"guide":[118],"LLMs":[119],"through":[120],"three":[121],"cognitive":[122],"stages:":[123],"factual":[124],"feature":[125],"extraction,":[126],"behavioral":[127],"pattern":[128],"analysis,":[129],"structured":[134],"output.":[135],"This":[136],"approach":[137],"addresses":[138],"the":[139],"scarcity":[140],"challenge":[141],"while":[146],"providing":[147],"transparent":[148],"chains.":[150],"Experimental":[151],"evaluation":[152],"real-world":[154],"demonstrates":[157],"achieves":[160],"competitive":[161],"performance":[162],"multiple":[164],"in":[167],"scenarios.":[169]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-30T00:00:00"}