{"id":"https://openalex.org/W7225328302","doi":"https://doi.org/10.1145/3767308.3836409","title":"GenTS: Unified Generative Modeling for Multimodal Time Series Analysis","display_name":"GenTS: Unified Generative Modeling for Multimodal Time Series Analysis","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7225328302","doi":"https://doi.org/10.1145/3767308.3836409"},"language":"en","primary_location":{"id":"doi:10.1145/3767308.3836409","doi":"https://doi.org/10.1145/3767308.3836409","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767308.3836409","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"ACM International Conference on Multimedia (ACM MM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3767308.3836409","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102860665","display_name":"Shuqi Gu","orcid":"https://orcid.org/0009-0001-7021-7171","observed_orcids":["https://orcid.org/0009-0001-7021-7171"]},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqi Gu","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-7021-7171","affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128200412","display_name":"Yongxiang Zhao","orcid":"https://orcid.org/0009-0006-2988-2483","observed_orcids":["https://orcid.org/0009-0006-2988-2483"]},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxiang Zhao","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-2988-2483","affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077678202","display_name":"Baoyu Jing","orcid":"https://orcid.org/0000-0003-1564-6499","observed_orcids":["https://orcid.org/0000-0003-1564-6499"]},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baoyu Jing","raw_affiliation_strings":["Meta, Menlo Park, California, USA"],"raw_orcid":"https://orcid.org/0000-0003-1564-6499","affiliations":[{"raw_affiliation_string":"Meta, Menlo Park, California, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102807475","display_name":"Kan Ren","orcid":"https://orcid.org/0000-0002-4032-9615","observed_orcids":["https://orcid.org/0000-0002-4032-9615"]},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kan Ren","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4032-9615","affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.86972302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2470","last_page":"2479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9970999956130981,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0017999999690800905,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0007999999797903001,"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/multimodal-time-series","display_name":"multimodal time series","score":0.9580000042915344},{"id":"https://openalex.org/keywords/generative-models","display_name":"generative models","score":0.7229999899864197},{"id":"https://openalex.org/keywords/data-scarcity","display_name":"data scarcity","score":0.5820000171661377},{"id":"https://openalex.org/keywords/temporal-understanding","display_name":"temporal understanding","score":0.6000000238418579}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6236000061035156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5296000242233276},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27900001406669617},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2667999863624573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3767308.3836409","doi":"https://doi.org/10.1145/3767308.3836409","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767308.3836409","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"ACM International Conference on Multimedia (ACM MM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3767308.3836409","doi":"https://doi.org/10.1145/3767308.3836409","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3767308.3836409","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"ACM International Conference on Multimedia (ACM MM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2604847698","https://openalex.org/W2752191396","https://openalex.org/W2766375149","https://openalex.org/W2802314367","https://openalex.org/W3092442149","https://openalex.org/W3132992987","https://openalex.org/W4283716478","https://openalex.org/W4310416691","https://openalex.org/W4312635677","https://openalex.org/W4320342418","https://openalex.org/W4323718951","https://openalex.org/W4382203079","https://openalex.org/W4385482868","https://openalex.org/W4390872297","https://openalex.org/W4391591184","https://openalex.org/W4391800490","https://openalex.org/W4392539799","https://openalex.org/W4392781393","https://openalex.org/W4393145940","https://openalex.org/W4396758709","https://openalex.org/W4396822597","https://openalex.org/W4398795597","https://openalex.org/W4403577884","https://openalex.org/W4407308611","https://openalex.org/W4407571440","https://openalex.org/W4409363714","https://openalex.org/W4409364177","https://openalex.org/W4412875496","https://openalex.org/W4414577766","https://openalex.org/W4415084307","https://openalex.org/W4415538258","https://openalex.org/W4415797235","https://openalex.org/W4416902891","https://openalex.org/W6929339258","https://openalex.org/W7088041907"],"related_works":["https://openalex.org/W2803925851","https://openalex.org/W4293787226","https://openalex.org/W7156130266","https://openalex.org/W7197051086","https://openalex.org/W4415797654","https://openalex.org/W7130721957","https://openalex.org/W4409097661","https://openalex.org/W7166565517","https://openalex.org/W7225322401","https://openalex.org/W2800788294"],"abstract_inverted_index":{"Modeling":[0],"multimodal":[1,63,86,127],"time":[2,64,82,96,112,119],"series":[3,65,83,97,113,120],"has":[4],"emerged":[5],"as":[6,17,31],"an":[7],"important":[8],"research":[9],"direction,":[10],"aiming":[11],"to":[12,20,37],"incorporate":[13],"auxiliary":[14],"modalities":[15,30],"such":[16],"textual":[18],"descriptions":[19],"enhance":[21],"temporal":[22],"understanding.":[23],"However,":[24],"existing":[25],"methods":[26],"often":[27],"treat":[28],"external":[29,99],"supplementary":[32],"features,":[33],"limiting":[34],"their":[35],"applicability":[36],"specific":[38],"tasks":[39,71],"and":[40,50,85,98,111,139],"resulting":[41],"in":[42,45],"high":[43],"costs":[44],"terms":[46],"of":[47,91,126,141],"design,":[48],"training,":[49],"maintenance.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"propose":[56],"GenTS,":[57],"a":[58,73],"unified":[59,102],"generative":[60],"framework":[61],"for":[62,80],"analysis":[66],"that":[67],"integrates":[68],"multiple":[69,145],"downstream":[70],"within":[72],"single":[74],"model.":[75],"GenTS":[76,122],"is":[77],"jointly":[78],"trained":[79],"text-conditioned":[81],"generation":[84],"forecasting,":[87,110],"enabling":[88],"effective":[89],"modeling":[90],"the":[92,124,137],"joint":[93],"distribution":[94],"between":[95],"modalities.":[100],"This":[101],"formulation":[103],"supports":[104],"diverse":[105,133],"applications,":[106],"including":[107],"conditional":[108],"generation,":[109],"editing.":[114],"Moreover,":[115],"by":[116],"incorporating":[117],"efficient":[118],"captioning,":[121],"alleviates":[123],"challenge":[125],"data":[128],"scarcity.":[129],"Extensive":[130],"experiments":[131],"on":[132],"real-world":[134],"datasets":[135],"demonstrate":[136],"effectiveness":[138],"generality":[140],"our":[142],"approach":[143],"across":[144],"tasks.":[146]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-06T00:00:00"}
