{"id":"https://openalex.org/W7136135546","doi":"https://doi.org/10.48550/arxiv.2603.12664","title":"From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space","display_name":"From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136135546","doi":"https://doi.org/10.48550/arxiv.2603.12664"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12664","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.12664","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129462365","display_name":"Lehui Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lehui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129397767","display_name":"Yuyao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129523102","display_name":"Jisheng Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Jisheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129399534","display_name":"Wei Emma Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000626453","display_name":"Jinliang Deng","orcid":"https://orcid.org/0000-0002-0759-947X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Jinliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038081609","display_name":"Haoliang Sun","orcid":"https://orcid.org/0000-0001-7715-5682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Haoliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129614937","display_name":"Zhongyi Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Zhongyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129409785","display_name":"Yongshun Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Yongshun","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/T11918","display_name":"Forecasting Techniques and Applications","score":0.24330000579357147,"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":0.24330000579357147,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.11980000138282776,"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/T10028","display_name":"Topic Modeling","score":0.10639999806880951,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.8274999856948853},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.7576000094413757},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7014999985694885},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5666999816894531},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.435699999332428},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4011000096797943},{"id":"https://openalex.org/keywords/formalism","display_name":"Formalism (music)","score":0.3962000012397766}],"concepts":[{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.8274999856948853},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.7576000094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.72079998254776},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7014999985694885},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5234000086784363},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5073999762535095},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C73301696","wikidata":"https://www.wikidata.org/wiki/Q5469984","display_name":"Formalism (music)","level":3,"score":0.3962000012397766},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C2986420190","wikidata":"https://www.wikidata.org/wiki/Q39045939","display_name":"Semantic space","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.335099995136261},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.3012000024318695},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12664","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12664","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Incorporating":[0],"textual":[1,20,55],"information":[2],"into":[3,57],"time-series":[4],"forecasting":[5,29,123],"holds":[6],"promise":[7],"for":[8],"addressing":[9],"event-driven":[10],"non-stationarity;":[11],"however,":[12],"a":[13,70,118],"fundamental":[14],"modality":[15],"gap":[16],"hinders":[17],"effective":[18],"fusion:":[19],"descriptions":[21],"express":[22],"temporal":[23,88],"impacts":[24],"implicitly":[25],"and":[26,34,50,94,105,129],"qualitatively,":[27],"whereas":[28],"models":[30],"rely":[31],"on":[32,111],"explicit":[33],"quantitative":[35],"signals.":[36],"Through":[37],"controlled":[38],"semi-synthetic":[39],"experiments,":[40],"we":[41,65],"show":[42],"that":[43],"existing":[44],"methods":[45],"over-attend":[46],"to":[47,52,117,126],"redundant":[48],"tokens":[49],"struggle":[51],"reliably":[53],"translate":[54],"semantics":[56],"usable":[58],"numerical":[59],"cues.":[60],"To":[61],"bridge":[62],"this":[63],"gap,":[64],"propose":[66],"TESS,":[67],"which":[68],"introduces":[69],"Temporal":[71],"Evolution":[72],"Semantic":[73],"Space":[74],"as":[75],"an":[76,100],"intermediate":[77],"bottleneck":[78],"between":[79],"modalities.":[80],"This":[81],"space":[82],"consists":[83],"of":[84],"interpretable,":[85],"numerically":[86],"grounded":[87],"primitives":[89],"(mean":[90],"shift,":[91],"volatility,":[92],"shape,":[93],"lag)":[95],"extracted":[96],"from":[97],"text":[98],"by":[99],"LLM":[101],"via":[102],"structured":[103],"prompting":[104],"filtered":[106],"through":[107],"confidence-aware":[108],"gating.":[109],"Experiments":[110],"four":[112],"real-world":[113],"datasets":[114],"demonstrate":[115],"up":[116],"29":[119],"percent":[120],"reduction":[121],"in":[122],"error":[124],"compared":[125],"state-of-the-art":[127],"unimodal":[128],"multimodal":[130],"baselines.":[131],"The":[132],"code":[133],"will":[134],"be":[135],"released":[136],"after":[137],"acceptance.":[138]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-17T00:00:00"}
