{"id":"https://openalex.org/W7128791682","doi":"https://doi.org/10.48550/arxiv.2602.11533","title":"AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting","display_name":"AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128791682","doi":"https://doi.org/10.48550/arxiv.2602.11533"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.11533","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125957543","display_name":"Zhihang Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuan, Zhihang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125984120","display_name":"Zhiyuan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhiyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5022046402","display_name":"Mahesh K. Marina","orcid":"https://orcid.org/0000-0002-6946-5143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marina, Mahesh K.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5125957543"],"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.3066999912261963,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.3066999912261963,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.22840000689029694,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision 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":0.11949999630451202,"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/spurious-relationship","display_name":"Spurious relationship","score":0.8059999942779541},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.697700023651123},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6894000172615051},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6183000206947327},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5005000233650208},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.48159998655319214},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41670000553131104}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.8059999942779541},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.697700023651123},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6894000172615051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6240000128746033},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6183000206947327},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5005000233650208},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41670000553131104},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40540000796318054},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38519999384880066},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27709999680519104},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2583000063896179},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.25679999589920044},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.11533","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.11533","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11533","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.11533","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.5204806923866272,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multivariate":[0],"time":[1,164],"series":[2,165],"forecasting":[3],"involves":[4],"two":[5,105],"qualitatively":[6],"distinct":[7],"factors:":[8],"(i)":[9],"stable":[10],"within-series":[11],"autoregressive":[12],"(AR)":[13],"dynamics,":[14],"and":[15,60,77,116],"(ii)":[16],"intermittent":[17],"cross-dimension":[18,47],"interactions":[19],"that":[20,29,53,73,126,144],"can":[21,49,155],"become":[22],"spurious":[23],"over":[24],"long":[25],"horizons.":[26],"We":[27],"argue":[28],"fitting":[30],"a":[31,70,89,97,157],"single":[32],"model":[33],"to":[34,112],"capture":[35],"both":[36],"effects":[37],"creates":[38],"an":[39],"optimization":[40,111,147],"conflict:":[41],"the":[42,51,83,93,104,133],"high-variance":[43],"updates":[44],"needed":[45],"for":[46],"modeling":[48],"corrupt":[50],"gradients":[52],"support":[54],"autoregression,":[55],"resulting":[56],"in":[57,162],"brittle":[58],"training":[59],"degraded":[61],"long-horizon":[62,138],"accuracy.":[63],"To":[64],"address":[65],"this,":[66],"we":[67],"propose":[68],"ALTTS,":[69,82],"dual-path":[71],"framework":[72],"explicitly":[74],"decouples":[75],"autoregression":[76],"cross-relation":[78],"(CR)":[79],"modeling.":[80],"In":[81],"AR":[84],"path":[85,95],"is":[86],"instantiated":[87],"with":[88,100,132],"linear":[90],"predictor,":[91],"while":[92],"CR":[94],"uses":[96],"Transformer":[98],"equipped":[99],"Cross-Relation":[101],"Self-Attention":[102],"(CRSA);":[103],"branches":[106],"are":[107],"coordinated":[108],"via":[109],"alternating":[110],"isolate":[113],"gradient":[114],"noise":[115],"reduce":[117],"cross-block":[118],"interference.":[119],"Extensive":[120],"experiments":[121],"on":[122,137],"multiple":[123],"benchmarks":[124],"show":[125],"ALTTS":[127],"consistently":[128],"outperforms":[129],"prior":[130],"methods,":[131],"most":[134],"pronounced":[135],"improvements":[136],"forecasting.":[139,166],"Overall,":[140],"our":[141],"results":[142],"suggest":[143],"carefully":[145],"designed":[146],"strategies,":[148],"rather":[149],"than":[150],"ever":[151],"more":[152],"complex":[153],"architectures,":[154],"be":[156],"key":[158],"driver":[159],"of":[160],"progress":[161],"multivariate":[163]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-14T00:00:00"}