{"id":"https://openalex.org/W7160630509","doi":"https://doi.org/10.48550/arxiv.2605.06361","title":"Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction","display_name":"Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160630509","doi":"https://doi.org/10.48550/arxiv.2605.06361"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06361","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2605.06361","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135705396","display_name":"Alessandro Pagani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pagani, Alessandro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022784496","display_name":"Marco Cominelli","orcid":"https://orcid.org/0000-0002-1838-348X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cominelli, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135655064","display_name":"Liying Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Liying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042789844","display_name":"Gaofeng Dong","orcid":"https://orcid.org/0000-0002-8206-3499"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Gaofeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004055341","display_name":"Sergio Benini","orcid":"https://orcid.org/0000-0003-2152-9424"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benini, Sergio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135692179","display_name":"Francesco Gringoli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gringoli, Francesco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052086841","display_name":"Mattia Savardi","orcid":"https://orcid.org/0000-0002-2751-5157"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Savardi, Mattia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101156993","display_name":"Mani B. Srivastava","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srivastava, Mani B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116174993","display_name":"Trevor Bihl","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bihl, Trevor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135692787","display_name":"Erik P. Blasch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blasch, Erik P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135704883","display_name":"Daniel O. Brigham","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brigham, Daniel O.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135691835","display_name":"Kara Combs","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Combs, Kara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022713560","display_name":"Lance Kaplan","orcid":"https://orcid.org/0000-0002-3627-4471"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaplan, Lance M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043937484","display_name":"Federico Cerutti","orcid":"https://orcid.org/0000-0003-0755-0358"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cerutti, Federico","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":0.2702000141143799,"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":0.2702000141143799,"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/T10788","display_name":"Neuroscience and Music Perception","score":0.05209999904036522,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.05079999938607216,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9394999742507935},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.588699996471405},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5181000232696533},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4677000045776367},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4302999973297119},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4154999852180481},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.41290000081062317},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.3497999906539917}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9394999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7228999733924866},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.588699996471405},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5181000232696533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5080999732017517},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4677000045776367},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3734000027179718},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3449999988079071},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.3084000051021576},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3009999990463257},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29350000619888306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28600001335144043},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.2849000096321106},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06361","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2605.06361","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06361","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,29],"preliminary":[4],"analysis":[5],"of":[6,9,33,88,115,157,177],"the":[7,44,60,85,105,111,119,134,173],"ability":[8],"Chronos":[10,79,158],"foundation":[11,178],"model":[12],"to":[13,62,104,168,171],"process":[14,24],"and":[15,41,50,113,137,162,166,175],"internally":[16],"represent":[17],"frequency":[18,116,135],"domain":[19],"information.":[20],"Foundation":[21],"models":[22,65,179],"that":[23],"time-series":[25],"data":[26],"offer":[27,152],"practitioners":[28],"unified":[30],"architecture":[31],"capable":[32],"learning":[34],"generic":[35],"temporal":[36,181],"representations":[37],"across":[38,53,133],"diverse":[39],"tasks":[40],"domains,":[42],"reducing":[43],"need":[45],"for":[46,110,155,180],"task-specific":[47],"feature":[48],"engineering":[49],"enabling":[51],"transfer":[52],"signal":[54,68,160],"modalities.":[55],"Despite":[56],"their":[57],"growing":[58],"adoption,":[59],"extent":[61],"which":[63,141],"such":[64],"encode":[66],"fundamental":[67],"properties":[69],"remains":[70],"insufficiently":[71],"characterised.":[72],"We":[73],"address":[74],"this":[75],"gap":[76],"by":[77],"analysing":[78],"under":[80],"controlled":[81],"conditions,":[82],"starting":[83],"from":[84],"simplest":[86],"class":[87],"signals:":[89],"discrete":[90],"sinusoids":[91],"generated":[92],"at":[93],"fixed":[94],"frequencies.":[95],"Using":[96],"lightweight":[97],"online":[98],"minimum":[99],"description":[100],"length":[101],"probes":[102],"applied":[103],"decoder":[106],"architecture,":[107],"we":[108],"test":[109],"presence":[112],"separability":[114],"information":[117,163],"in":[118,140,159],"model's":[120],"internal":[121],"representations.":[122],"The":[123],"results":[124],"provide":[125],"insight":[126],"into":[127],"how":[128],"frequential":[129],"content":[130],"is":[131],"captured":[132],"spectrum":[136],"highlight":[138],"regimes":[139],"representation":[142],"quality":[143],"may":[144],"degrade":[145],"or":[146],"require":[147],"particular":[148],"care.":[149],"These":[150],"findings":[151],"practical":[153],"guidance":[154],"users":[156],"processing":[161],"fusion":[164],"contexts,":[165],"contribute":[167],"ongoing":[169],"efforts":[170],"improve":[172],"interpretability":[174],"evaluation":[176],"data.":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}