{"id":"https://openalex.org/W7162804892","doi":"https://doi.org/10.48550/arxiv.2605.28888","title":"Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap","display_name":"Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162804892","doi":"https://doi.org/10.48550/arxiv.2605.28888"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28888","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":null,"license_id":null,"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.2605.28888","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137347792","display_name":"Sicong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Sicong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137394112","display_name":"Ruiting Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Ruiting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137354518","display_name":"Yue Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137339293","display_name":"Bowen Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Bowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074851506","display_name":"Jun Meng","orcid":"https://orcid.org/0000-0002-4087-893X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137377671","display_name":"Jie Li","orcid":"https://orcid.org/0000-0002-0952-093X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137361857","display_name":"Shuaijun Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Shuaijun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137394013","display_name":"Yu Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137352816","display_name":"Fanyi Di","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di, Fanyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137323292","display_name":"Xin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xin","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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.41940000653266907,"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"}},"topics":[{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.41940000653266907,"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"}},{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.12229999899864197,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.062300000339746475,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.715499997138977},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6535999774932861},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.612500011920929},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5358999967575073},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4787999987602234},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.40139999985694885},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.38510000705718994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638000249862671},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.715499997138977},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6535999774932861},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.612500011920929},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5358999967575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167999863624573},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.40139999985694885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3352000117301941},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C193856179","wikidata":"https://www.wikidata.org/wiki/Q5251100","display_name":"Defeasible estate","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3091000020503998},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29499998688697815},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28888","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.28888","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28888","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-world":[0],"user":[1],"behavior":[2],"rarely":[3],"consists":[4],"of":[5,28],"isolated":[6],"actions;":[7],"instead,":[8],"it":[9],"often":[10],"forms":[11],"intent":[12,39],"flows":[13],"governed":[14],"by":[15,65],"spatiotemporal":[16,50,159],"dependencies.":[17],"To":[18,75],"provide":[19],"integrated":[20],"service":[21],"recommendations,":[22],"we":[23,79,103,142,155],"focus":[24],"on":[25],"the":[26,134,149,184],"task":[27],"Generative":[29],"Spatiotemporal":[30,144],"Intent":[31],"Sequence":[32],"Recommendation":[33],"(GSISR),":[34],"which":[35,109],"aims":[36],"to":[37,96,121,132,158],"generate":[38],"sequences":[40],"that":[41,85,172],"are":[42,188],"logically":[43],"coherent":[44],"and":[45,69,139,161,167,178,183],"physically":[46,72],"executable":[47],"within":[48],"complex":[49,123],"contexts.":[51],"While":[52],"LLMs":[53],"offer":[54],"strong":[55],"reasoning":[56,88,98,112,129],"potential":[57],"for":[58],"GSISR,":[59],"direct":[60],"industrial":[61],"deployment":[62],"is":[63],"limited":[64],"high":[66],"inference":[67],"latency":[68,101],"context-mismatched":[70,163],"or":[71],"infeasible":[73],"plans.":[74,164],"address":[76,133],"these":[77],"challenges,":[78],"propose":[80],"a":[81],"generative":[82],"framework,":[83],"GPlan,":[84],"internalizes":[86],"LLM":[87],"into":[89,114],"lightweight":[90],"models":[91,120],"through":[92],"two":[93],"components.":[94],"First,":[95],"enable":[97],"under":[99],"strict":[100],"constraints,":[102,141],"introduce":[104],"Progressive":[105],"Implicit":[106],"CoT":[107],"Distillation,":[108],"compresses":[110],"explicit":[111],"processes":[113],"reserved":[115],"latent":[116],"tokens,":[117],"allowing":[118],"small":[119],"inherit":[122],"planning":[124],"logic":[125],"without":[126],"generating":[127],"long":[128],"text.":[130],"Second,":[131],"disconnect":[135],"between":[136],"general":[137],"knowledge":[138],"real-world":[140],"design":[143],"Counterfactual":[145],"DPO.":[146],"By":[147],"aligning":[148],"model":[150],"with":[151],"counterfactual":[152],"context-plan":[153],"pairs,":[154],"improve":[156],"sensitivity":[157],"context":[160,179],"reduce":[162],"Offline":[165],"experiments":[166],"online":[168],"A/B":[169],"testing":[170],"demonstrate":[171],"our":[173],"approach":[174],"improves":[175],"sequence":[176],"coherence":[177],"responsiveness.":[180],"Our":[181],"implementation":[182],"anonymized":[185],"GSISR":[186],"dataset":[187],"available":[189],"at":[190],"https://github.com/alibaba/GPlan.":[191]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-30T00:00:00"}