{"id":"https://openalex.org/W7163568335","doi":"https://doi.org/10.48550/arxiv.2606.04074","title":"Adaptive Patching Is Harder Than It Looks For Time-Series Forecasting","display_name":"Adaptive Patching Is Harder Than It Looks For Time-Series Forecasting","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163568335","doi":"https://doi.org/10.48550/arxiv.2606.04074"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04074","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04074","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":null,"license_id":null,"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.2606.04074","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132566846","display_name":"Federico Zucchi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zucchi, Federico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137816377","display_name":"Yi Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137851522","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0001-7455-6640"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137859390","display_name":"Keyuan Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Keyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137910589","display_name":"Thomas Lampert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lampert, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137826173","display_name":"Ziyue Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ziyue","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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.446399986743927,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.446399986743927,"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"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.1876000016927719,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.15369999408721924,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.6330000162124634},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5310999751091003},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5005000233650208},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.38839998841285706},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.33799999952316284},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.3158999979496002}],"concepts":[{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.6330000162124634},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5530999898910522},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5005000233650208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48100000619888306},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35989999771118164},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.3158999979496002},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31029999256134033},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.2985999882221222},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C2776003309","wikidata":"https://www.wikidata.org/wiki/Q1988072","display_name":"Adaptive algorithm","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.26350000500679016}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04074","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04074","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.04074","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04074","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Adaptive":[0,219],"patching":[1,28,55,61,75,220],"is":[2,39,49,129,186],"a":[3,26,32,46,63,73,81,109,117,121,140,151,164,226,235],"recent":[4],"and":[5,67,95,125,173,198,217,237],"compelling":[6],"proposal":[7],"for":[8],"time-series":[9],"Transformers:":[10],"allocate":[11],"finer":[12,54,244],"patches":[13,245],"where":[14,53,243],"the":[15,57,87,101,127,135,170,182,189],"sequence":[16],"looks":[17],"locally":[18,91],"informative.":[19],"This":[20],"paper":[21],"asks":[22],"under":[23,42,100,120],"what":[24],"conditions":[25],"content-adaptive":[27],"operator":[29],"should":[30,221],"outperform":[31],"tuned":[33,227],"uniform":[34,83,142,165,184,228],"one.":[35],"Local":[36],"heterogeneity":[37],"alone":[38],"not":[40,50],"enough:":[41],"pointwise":[43],"forecasting":[44,180,248],"losses,":[45],"complex-looking":[47],"region":[48],"automatically":[51],"one":[52],"reduces":[56],"loss.":[58,249],"We":[59],"model":[60],"as":[62],"budgeted":[64],"bitrate":[65],"allocation":[66],"derive":[68],"an":[69],"explicit":[70],"threshold":[71],"that":[72],"dynamic":[74,190],"rule":[76],"must":[77],"satisfy":[78],"to":[79,131],"beat":[80],"well-tuned":[82,141],"baseline,":[84],"then":[85],"bound":[86,99],"achievable":[88],"improvement":[89],"both":[90],"(a":[92,97],"quadratic":[93],"surrogate)":[94],"globally":[96],"strong-convexity":[98],"model's":[102],"assumptions).":[103],"Two":[104],"structural":[105],"results":[106,204],"follow:":[107],"without":[108],"coupling":[110],"constraint,":[111],"scalar":[112],"local":[113],"complexity":[114],"cannot":[115],"produce":[116],"non-uniform":[118],"optimum":[119],"common":[122],"loss":[123],"landscape;":[124],"once":[126,203],"backbone":[128],"trained":[130],"its":[132,230],"representation-aware":[133],"optimum,":[134],"alignment":[136],"gain":[137],"collapses":[138],"around":[139],"patch":[143],"size.":[144],"To":[145],"test":[146],"these":[147],"predictions,":[148],"we":[149,212],"run":[150],"controlled":[152],"isolation":[153],"study":[154],"on":[155,233],"three":[156],"representative":[157],"architectures,":[158],"replacing":[159],"each":[160],"adaptive":[161],"mechanism":[162],"with":[163,188,192],"patch-size":[166],"sweep":[167],"while":[168],"keeping":[169],"backbone,":[171],"data,":[172],"training":[174],"protocol":[175],"fixed.":[176],"On":[177],"standard":[178],"long-horizon":[179],"benchmarks,":[181],"validation-selected":[183],"baseline":[185],"competitive":[187],"counterpart,":[191],"per-setting":[193],"effects":[194],"concentrated":[195],"near":[196],"zero":[197],"no":[199],"consistent":[200],"directional":[201],"advantage":[202],"are":[205,215],"aggregated":[206],"by":[207],"dataset.":[208],"The":[209],"larger":[210],"gains":[211],"do":[213],"observe":[214],"method-":[216],"dataset-specific.":[218],"therefore":[222],"be":[223],"evaluated":[224],"against":[225],"baseline;":[229],"value":[231],"depends":[232],"whether":[234],"cheap":[236],"reliable":[238],"routing":[239],"signal":[240],"can":[241],"identify":[242],"actually":[246],"reduce":[247]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-05T00:00:00"}
