{"id":"https://openalex.org/W4414359502","doi":"https://doi.org/10.24963/ijcai.2025/1173","title":"Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era","display_name":"Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359502","doi":"https://doi.org/10.24963/ijcai.2025/1173"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/1173","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/1173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5100387427","display_name":"Chenxi Liu","orcid":"https://orcid.org/0000-0002-9134-1235"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chenxi Liu","raw_affiliation_strings":["S-Lab, Nanyang Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088311182","display_name":"Shaowen Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shaowen Zhou","raw_affiliation_strings":["S-Lab, Nanyang Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002044458","display_name":"Qianxiong Xu","orcid":"https://orcid.org/0000-0001-9175-6783"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Qianxiong Xu","raw_affiliation_strings":["S-Lab, Nanyang Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100743269","display_name":"Miao Hao","orcid":"https://orcid.org/0000-0002-8386-2145"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Hao Miao","raw_affiliation_strings":["Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044528555","display_name":"Cheng Long","orcid":"https://orcid.org/0000-0001-6806-8405"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Cheng Long","raw_affiliation_strings":["S-Lab, Nanyang Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111259477","display_name":"Ziyue Li","orcid":"https://orcid.org/0009-0004-3677-2886"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ziyue Li","raw_affiliation_strings":["Technical University of Munich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101987526","display_name":"Rui Zhao","orcid":"https://orcid.org/0000-0002-9699-9984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rui Zhao","raw_affiliation_strings":["SenseTime Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.5534,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.97937389,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"10564","last_page":"10572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9902999997138977,"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":0.9902999997138977,"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/time-series","display_name":"Time series","score":0.5975000262260437},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.57669997215271},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5734999775886536},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4902999997138977},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4781999886035919},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.39980000257492065},{"id":"https://openalex.org/keywords/data-type","display_name":"Data type","score":0.3815999925136566}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699999988079071},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6676999926567078},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5975000262260437},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.57669997215271},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5734999775886536},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4902999997138977},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37380000948905945},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2815999984741211},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2025/1173","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/1173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/26d49762-6db5-4d0c-81d6-25838c3922f3","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/26d49762-6db5-4d0c-81d6-25838c3922f3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Liu, C, Zhou, S, Xu, Q, Miao, H, Long, C, Li, Z & Zhao, R 2025, Towards Cross-Modality Modeling for Time Series Analytics : A Survey in the LLM Era. in J Kwok (ed.), Proceedings of the 34th International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 10564-10572, 34th International Joint Conference on Artificial Intelligence, Montreal, Canada, 16/08/2025. https://doi.org/10.24963/ijcai.2025/1173","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"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":{"The":[0],"proliferation":[1],"of":[2,10,20,44,93,117,142,160,187],"edge":[3],"devices":[4],"has":[5],"generated":[6],"an":[7,90],"unprecedented":[8],"volume":[9],"time":[11,35,48,56,74,98,122,168,195],"series":[12,36,57,99,123,169,196],"data":[13,46,119,162],"across":[14,139],"different":[15,153],"domains,":[16],"motivating":[17],"a":[18,31,51,104,140,185],"variety":[19],"well-customized":[21],"methods.":[22],"Recently,":[23],"Large":[24],"Language":[25],"Models":[26],"(LLMs)":[27],"have":[28],"emerged":[29],"as":[30,61],"new":[32],"paradigm":[33],"for":[34,73,97,121,166,177,184],"analytics":[37],"by":[38],"leveraging":[39],"the":[40,115],"shared":[41],"sequential":[42],"nature":[43],"textual":[45,66,118,161],"and":[47,58,68,133,135,163,190],"series.":[49,75],"However,":[50],"fundamental":[52],"cross-modality":[53,95,129,164],"gap":[54],"between":[55],"LLMs":[59,62],"exists,":[60],"are":[63,69,79],"pre-trained":[64],"on":[65,114,149],"corpora":[67],"not":[70],"inherently":[71],"optimized":[72],"Many":[76],"recent":[77],"proposals":[78],"designed":[80,183],"to":[81,156],"address":[82],"this":[83,86],"issue.":[84],"In":[85],"survey,":[87],"we":[88,146,172],"provide":[89],"up-to-date":[91],"overview":[92],"LLMs-based":[94],"modeling":[96],"analytics.":[100,170],"We":[101,125],"first":[102],"introduce":[103],"taxonomy":[105],"that":[106],"classifies":[107],"existing":[108],"approaches":[109],"into":[110],"four":[111],"groups":[112],"based":[113],"type":[116],"employed":[120],"modeling.":[124,197],"then":[126],"summarize":[127],"key":[128],"strategies,":[130],"e.g.,":[131],"alignment":[132],"fusion,":[134],"discuss":[136],"their":[137],"applications":[138],"range":[141,186],"downstream":[143],"tasks.":[144],"Furthermore,":[145],"conduct":[147],"experiments":[148],"multimodal":[150],"datasets":[151],"from":[152],"application":[154],"domains":[155],"investigate":[157],"effective":[158],"combinations":[159],"strategies":[165],"enhancing":[167],"Finally,":[171],"suggest":[173],"several":[174],"promising":[175],"directions":[176],"future":[178],"research.":[179],"This":[180],"survey":[181],"is":[182],"professionals,":[188],"researchers,":[189],"practitioners":[191],"interested":[192],"in":[193],"LLM-based":[194]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
