{"id":"https://openalex.org/W7164055022","doi":"https://doi.org/10.48550/arxiv.2606.08122","title":"Think Before You Act: Intention-Guided Reasoning for LLM-Based Location Prediction","display_name":"Think Before You Act: Intention-Guided Reasoning for LLM-Based Location Prediction","publication_year":2026,"publication_date":"2026-06-06","ids":{"openalex":"https://openalex.org/W7164055022","doi":"https://doi.org/10.48550/arxiv.2606.08122"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08122","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.08122","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138201834","display_name":"Qingxiang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Qingxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138255240","display_name":"Anqi Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Anqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138226819","display_name":"Zhuoyang Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhuoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059494004","display_name":"Yutian Jiang","orcid":"https://orcid.org/0009-0008-3800-1144"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yutian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119959702","display_name":"Sisuo Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyu, Sisuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138270300","display_name":"Yu Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138263656","display_name":"Haomin Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Haomin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138222224","display_name":"Yuxuan Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.6363000273704529,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.6363000273704529,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.28369998931884766,"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/T11904","display_name":"Spatial Cognition and Navigation","score":0.012199999764561653,"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/inference","display_name":"Inference","score":0.6190999746322632},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5594000220298767},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5533000230789185},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5297999978065491},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5285000205039978},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.43290001153945923}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421000003814697},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6190999746322632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5800999999046326},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5594000220298767},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5533000230789185},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5285000205039978},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3596000075340271},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3021000027656555},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08122","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.08122","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08122","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Predicting":[0],"a":[1,13,41,71,87,120],"user's":[2],"next":[3,150],"Point-of-Interest":[4],"(POI)":[5],"based":[6],"on":[7,162],"their":[8],"historical":[9,54,103],"check-in":[10],"records":[11],"is":[12],"fundamental":[14],"task":[15,39],"in":[16],"location-based":[17],"services.":[18],"While":[19],"recent":[20],"methods":[21],"incorporating":[22,102],"large":[23],"language":[24],"models":[25],"have":[26],"shown":[27],"strong":[28],"reasoning":[29,90,128],"capabilities":[30],"and":[31,53,65,74,109,124],"promising":[32],"results,":[33],"they":[34,67],"typically":[35],"formulate":[36],"the":[37,93,110,114,136,149],"prediction":[38,152],"as":[40],"one-step":[42],"trajectory-to-location":[43],"mapping":[44],"problem,":[45],"making":[46],"predictions":[47],"prone":[48],"to":[49,129],"shallow":[50],"trajectory":[51,155],"correlations":[52],"frequency":[55],"bias.":[56],"We":[57],"argue":[58],"that":[59,132,167],"users":[60],"rarely":[61],"choose":[62],"locations":[63,131],"directly":[64],"instead,":[66],"usually":[68],"first":[69,118],"form":[70],"traveling":[72],"intention":[73,142],"then":[75,125],"accordingly":[76],"select":[77],"specific":[78],"POIs.":[79],"Motivated":[80],"by":[81,101],"this":[82],"insight,":[83],"we":[84,96,117],"propose":[85],"IntentPOI,":[86],"two-stage":[88],"intention-guided":[89,127,158],"framework.":[91],"In":[92,113],"thinking":[94],"stage,":[95,116],"infer":[97],"users'":[98],"intermediate":[99],"intentions":[100],"mobility":[104],"patterns,":[105],"similar":[106],"peer":[107],"behaviors,":[108],"temporal":[111],"contexts.":[112],"acting":[115],"construct":[119],"compact":[121],"candidate":[122],"pool,":[123],"perform":[126],"identify":[130],"best":[133],"align":[134],"with":[135],"inferred":[137],"intention.":[138],"By":[139],"explicitly":[140],"decoupling":[141],"inference":[143],"from":[144,153],"location":[145],"prediction,":[146],"IntentPOI":[147,168],"transforms":[148],"POI":[151],"direct":[154],"matching":[156],"into":[157],"reasoning.":[159],"Extensive":[160],"experiments":[161],"three":[163],"real-world":[164],"datasets":[165],"demonstrate":[166],"consistently":[169],"outperforms":[170],"eleven":[171],"state-of-the-art":[172],"baselines.":[173]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}
