{"id":"https://openalex.org/W7134810089","doi":"https://doi.org/10.48550/arxiv.2603.08349","title":"Towards plausibility in time series counterfactual explanations","display_name":"Towards plausibility in time series counterfactual explanations","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134810089","doi":"https://doi.org/10.48550/arxiv.2603.08349"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.08349","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128636880","display_name":"Marcin Kostrzewa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kostrzewa, Marcin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128633669","display_name":"Krzysztof Galus","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Galus, Krzysztof","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128680773","display_name":"Maciej Zi\u0119ba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zi\u0119ba, Maciej","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":0.9449999928474426,"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":0.9449999928474426,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0052999998442828655,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.0032999999821186066,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9569000005722046},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.9435999989509583},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6173999905586243},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.531499981880188},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4674000144004822}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9569000005722046},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.9435999989509583},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6173999905586243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6087999939918518},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.454800009727478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44620001316070557},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41179999709129333},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.08349","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.08349","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08349","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.08349","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"We":[0,82],"present":[1],"a":[2,50,59,133],"new":[3],"method":[4,88,110,154],"for":[5,10,71,159],"generating":[6],"plausible":[7,171],"counterfactual":[8,66,157],"explanations":[9,158],"time":[11,32,160],"series":[12,161],"classification":[13],"problems.":[14],"The":[15,54,105],"approach":[16],"performs":[17],"gradient-based":[18],"optimization":[19,56],"directly":[20],"in":[21,114,121,143],"the":[22,39,45,77,95,99,125,137,152],"input":[23],"space.":[24],"To":[25],"enforce":[26],"plausibility,":[27],"we":[28],"integrate":[29],"soft-DTW":[30],"(dynamic":[31],"warping)":[33],"alignment":[34,123],"with":[35,124,174],"$k$-nearest":[36],"neighbors":[37],"from":[38],"target":[40,126],"class,":[41,127],"which":[42],"effectively":[43],"encourages":[44],"generated":[46,100],"counterfactuals":[47,101],"to":[48],"adopt":[49],"realistic":[51,145],"temporal":[52,130,146,175],"structure.":[53,147],"overall":[55],"objective":[57],"is":[58],"multi-faceted":[60],"loss":[61],"function":[62],"that":[63,108,151,163],"balances":[64],"key":[65,96],"properties.":[67],"It":[68],"incorporates":[69],"losses":[70],"validity,":[72],"sparsity,":[73],"and":[74,172],"proximity,":[75],"alongside":[76],"novel":[78],"soft-DTW-based":[79],"plausibility":[80],"component.":[81],"conduct":[83],"an":[84],"evaluation":[85],"of":[86,98,140],"our":[87,109],"against":[89],"several":[90],"strong":[91],"reference":[92],"approaches,":[93],"measuring":[94],"properties":[97],"across":[102],"multiple":[103],"dimensions.":[104],"results":[106],"demonstrate":[107],"achieves":[111],"competitive":[112],"performance":[113],"validity":[115],"while":[116],"significantly":[117],"outperforming":[118],"existing":[119,141],"approaches":[120],"distributional":[122],"indicating":[128],"superior":[129],"realism.":[131],"Furthermore,":[132],"qualitative":[134],"analysis":[135],"highlights":[136],"critical":[138],"limitations":[139],"methods":[142],"preserving":[144],"This":[148],"work":[149],"shows":[150],"proposed":[153],"consistently":[155],"generates":[156],"classifiers":[162],"are":[164],"not":[165],"only":[166],"valid":[167],"but":[168],"also":[169],"highly":[170],"consistent":[173],"patterns.":[176]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-11T00:00:00"}
