{"id":"https://openalex.org/W7125164849","doi":"https://doi.org/10.5281/zenodo.17787289","title":"Open Science Artifact - FedOverlap: A Weight Overlap Approach to Model Repair in Federated Learning","display_name":"Open Science Artifact - FedOverlap: A Weight Overlap Approach to Model Repair in Federated Learning","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125164849","doi":"https://doi.org/10.5281/zenodo.17787289"},"language":null,"primary_location":{"id":"doi:10.5281/zenodo.17787289","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17787289","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.17787289","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Anonymous Authors","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Anonymous Authors","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":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/codebase","display_name":"Codebase","score":0.6074000000953674},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.554099977016449},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5268999934196472},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.3352000117301941},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.32589998841285706},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.3244999945163727},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.31450000405311584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8188999891281128},{"id":"https://openalex.org/C51929080","wikidata":"https://www.wikidata.org/wiki/Q2425187","display_name":"Codebase","level":3,"score":0.6074000000953674},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.554099977016449},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.43389999866485596},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.3285999894142151},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32589998841285706},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31369999051094055},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.30379998683929443},{"id":"https://openalex.org/C3018397939","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Open source","level":3,"score":0.2824000120162964},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C97250363","wikidata":"https://www.wikidata.org/wiki/Q235557","display_name":"File format","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C199672914","wikidata":"https://www.wikidata.org/wiki/Q4241353","display_name":"Hot spot (computer programming)","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C171730128","wikidata":"https://www.wikidata.org/wiki/Q5227290","display_name":"Data file","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.17787289","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17787289","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"Dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.17787289","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17787289","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"Dataset"},"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],"package":[1,35],"contains":[2,36],"the":[3,8,11,15,37,44,55,76,104,111,121,124,128,131,137,144,150,154,157],"codebase":[4],"for":[5,86,110,119,135],"FedOverlap":[6,58,67],"and":[7,59,68,101,107,126,140],"results":[9,122,155],"of":[10,123,130,156],"experiments":[12,56,125],"reported":[13],"in":[14,26,143],"paper":[16],"\"FedOverlap:":[17],"A":[18,83,115],"Federated":[19,27],"Weight":[20],"Overlap":[21],"Approach":[22],"to":[23,42,50,53,64,74,92],"Model":[24],"Repair":[25],"Learning\",":[28],"which":[29],"is":[30],"currently":[31],"under":[32],"revision.":[33],"The":[34,62,72],"following":[38],"file:":[39],"README.md:":[40],"Instructions":[41],"reproduce":[43],"entire":[45],"study":[46],"pipeline.":[47],"Please":[48],"refer":[49],"this":[51],"file":[52,118],"run":[54,65,75],"with":[57,153],"FedRepair;":[60],"main.py:":[61],"script":[63,73],"both":[66],"FedRepair":[69],"approaches;":[70],"sensitive-analysis-rq5.py:":[71],"sensitive":[77],"analysis":[78],"(RQ5)":[79],"on":[80],"FedOverlap;":[81],"Preliminary_Analysis.ipynb:":[82],"Jupyter":[84,116],"notebook":[85,117],"Section":[87],"5.1":[88],"(Preliminary":[89],"Analysis),":[90],"used":[91],"(i)":[93],"analyze":[94],"per-class":[95],"performance":[96],"after":[97],"baseline":[98],"federated":[99],"training":[100],"(ii)":[102],"select":[103],"target":[105],"classes":[106],"experimental":[108],"parameters":[109],"repair":[112],"study.":[113],"Paper_Figures.ipynb:":[114],"pre-processing":[120],"generating":[127],"plots":[129,139],"paper;":[132,145],"img/:":[133],"Folder":[134,148],"saving":[136],"output":[138],"tables":[141],"present":[142],"Paper":[146],"Results/:":[147],"containing":[149],".csv":[151],"files":[152],"experiments.":[158]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-01-22T00:00:00"}