{"id":"https://openalex.org/W7161084841","doi":"https://doi.org/10.48550/arxiv.2605.12200","title":"Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS","display_name":"Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161084841","doi":"https://doi.org/10.48550/arxiv.2605.12200"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.12200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12200","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.2605.12200","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092241331","display_name":"Gaspard Berthelier","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berthelier, Gaspard","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136021611","display_name":"Mariia Baranova","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baranova, Mariia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120324913","display_name":"Andrei-Tiberiu Pantea","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pantea, Andrei-Tiberiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136065387","display_name":"Etienne Le Naour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naour, Etienne Le","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091982955","display_name":"Adrien Petralia","orcid":"https://orcid.org/0000-0003-2987-9111"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Petralia, Adrien","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052313903","display_name":"Tahar Nabil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nabil, Tahar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136074185","display_name":"Themis Palpanas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Palpanas, Themis","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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.6140999794006348,"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":0.6140999794006348,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.0421999990940094,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.03440000116825104,"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/simple","display_name":"Simple (philosophy)","score":0.7932999730110168},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5909000039100647},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5746999979019165},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.33649998903274536}],"concepts":[{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.7932999730110168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6639000177383423},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5909000039100647},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5746999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46459999680519104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3779999911785126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3386000096797943},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30379998683929443},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2906999886035919}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.12200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12200","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.2605.12200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12200","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":[{"score":0.5937766432762146,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Time":[0],"Series":[1],"Foundation":[2],"Models":[3],"(TSFMs)":[4],"have":[5],"recently":[6],"achieved":[7],"state-of-the-art":[8],"performance,":[9],"often":[10],"outperforming":[11],"supervised":[12],"models":[13],"in":[14],"zero-shot":[15],"settings.":[16],"Recent":[17],"TSFM":[18],"architectures,":[19],"such":[20],"as":[21],"Chronos-2":[22,69],"and":[23],"TabPFN-TS,":[24],"aim":[25],"to":[26,41],"integrate":[27],"covariates.":[28],"In":[29],"this":[30,43],"paper,":[31],"we":[32],"design":[33],"controlled":[34],"experiments":[35],"based":[36],"on":[37],"simple":[38,78],"target-covariate":[39],"relationships":[40,53],"assess":[42],"integration":[44],"capability.":[45],"Our":[46],"results":[47],"show":[48],"that":[49,63],"TabPFN-TS":[50],"captures":[51],"these":[52],"more":[54],"effectively":[55],"than":[56],"Chronos-2,":[57],"especially":[58],"for":[59],"short":[60],"horizons,":[61],"suggesting":[62],"the":[64],"strong":[65],"benchmark":[66],"performance":[67],"of":[68,77],"does":[70],"not":[71],"automatically":[72],"translate":[73],"into":[74],"optimal":[75],"modeling":[76],"covariate-target":[79],"dependencies.":[80]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-14T00:00:00"}
