{"id":"https://openalex.org/W4415971128","doi":"https://doi.org/10.1109/lsp.2025.3630087","title":"Transformer-PLM Enhanced Multimodal Time Series Forecasting via Decoupled Dual-Temporal Graph Adaptation","display_name":"Transformer-PLM Enhanced Multimodal Time Series Forecasting via Decoupled Dual-Temporal Graph Adaptation","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W4415971128","doi":"https://doi.org/10.1109/lsp.2025.3630087"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2025.3630087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3630087","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jierui Lei","orcid":"https://orcid.org/0009-0006-4972-6920"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jierui Lei","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-4972-6920","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenjian Zhang","orcid":"https://orcid.org/0009-0001-5548-9515"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjian Zhang","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0001-5548-9515","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]},{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100942627","display_name":"Qingyi Yang","orcid":"https://orcid.org/0009-0000-9502-335X"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyi Yang","raw_affiliation_strings":["School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]},{"raw_affiliation_string":"School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xudong Zhang","orcid":"https://orcid.org/0009-0001-0684-105X"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Zhang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-0684-105X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110364708","display_name":"Haina Tang","orcid":"https://orcid.org/0000-0002-7150-0243"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haina Tang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7150-0243","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12032995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"11","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.44020000100135803,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.44020000100135803,"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/T10028","display_name":"Topic Modeling","score":0.11159999668598175,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.1071000024676323,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/plug-in","display_name":"Plug-in","score":0.5103999972343445},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5047000050544739},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.49869999289512634},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.49309998750686646},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47620001435279846},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4203000068664551},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4196000099182129},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.37470000982284546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7736999988555908},{"id":"https://openalex.org/C4924752","wikidata":"https://www.wikidata.org/wiki/Q184148","display_name":"Plug-in","level":2,"score":0.5103999972343445},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5047000050544739},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49309998750686646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48350000381469727},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47620001435279846},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3398999869823456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3294000029563904},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2800000011920929},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.27309998869895935},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3630087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3630087","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1262453860","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u8239\u8236\u8f68\u8ff9\u5f02\u5e38\u6a21\u5f0f\u6316\u6398\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"52071312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2026619093","https://openalex.org/W2337744400","https://openalex.org/W2896457183","https://openalex.org/W2965341826","https://openalex.org/W3022643593","https://openalex.org/W3023881809","https://openalex.org/W3080253043","https://openalex.org/W3094502228","https://openalex.org/W3176273155","https://openalex.org/W3177318507","https://openalex.org/W3181231283","https://openalex.org/W3204801262","https://openalex.org/W4226470037","https://openalex.org/W4309409002","https://openalex.org/W4376226279","https://openalex.org/W4382203079","https://openalex.org/W4385245566","https://openalex.org/W4385258623","https://openalex.org/W4390143397","https://openalex.org/W4393145940","https://openalex.org/W4393147362","https://openalex.org/W4396877909","https://openalex.org/W4401567681","https://openalex.org/W4401863317","https://openalex.org/W4401863947","https://openalex.org/W4402011156","https://openalex.org/W4403600951","https://openalex.org/W4408353533","https://openalex.org/W4415797300"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,138],"proliferation":[2],"of":[3,32,140],"multimodal":[4,34],"data":[5],"in":[6,54,102,122],"real-world":[7],"applications,":[8],"integrating":[9],"time":[10,35],"series":[11,36,87],"with":[12],"auxiliary":[13],"modalities":[14],"has":[15],"become":[16],"critical":[17],"for":[18,82],"accurate":[19],"forecasting.":[20],"Although":[21],"Transformers":[22],"and":[23,67,109,119,134],"pre-trained":[24],"language":[25],"model":[26,64],"(PLM)":[27],"have":[28],"enabled":[29],"initial":[30],"explorations":[31],"multi-domain":[33],"analysis,":[37],"several":[38],"pressing":[39],"challenges":[40],"still":[41],"remain.":[42],"Specifically,":[43],"coarse-grained":[44],"alignment":[45],"may":[46],"hinder":[47],"long-range":[48],"semantic":[49,107,127],"capture,":[50],"while":[51],"distribution":[52],"shifts":[53],"intra-modality":[55],"introduce":[56],"fluctuating":[57],"noise.":[58],"Inspired":[59],"by":[60],"GNNs'":[61],"capability":[62],"to":[63],"spatio-temporal":[65],"dependencies":[66],"contextual":[68,117],"interactions,":[69],"we":[70],"propose":[71],"Decoupled":[72],"Dual":[73],"Adaptive":[74],"Temporal":[75],"Graph":[76],"(DDATG),":[77],"a":[78],"universal":[79],"GNN":[80],"plugin":[81],"Transformer-PLM":[83],"based":[84],"adaptive":[85],"text-time":[86],"bimodal":[88],"learning.":[89],"Our":[90],"framework:":[91],"(1)":[92],"Reconstructs":[93],"global":[94],"temporal":[95,103],"patterns":[96],"from":[97],"decoupled":[98],"local":[99],"residual":[100],"terms":[101],"modality,":[104,124],"enhancing":[105],"local-global":[106],"discovery":[108],"diversifying":[110],"attention":[111],"mechanisms;":[112],"(2)":[113],"Explicitly":[114],"constructs":[115],"pointwise":[116],"connections":[118],"strengthens":[120],"aggregation":[121],"textual":[123],"facilitating":[125],"inter-modal":[126],"alignment.":[128],"Extensive":[129],"experiments":[130],"across":[131],"Transformer":[132],"variants":[133],"domain-specific":[135],"datasets":[136],"demonstrate":[137],"effectiveness":[139],"DDATG.":[141],"Code":[142],"is":[143],"available":[144],"athttps://github.com/DDATG.":[145]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-11-06T00:00:00"}
