{"id":"https://openalex.org/W4416707750","doi":"https://doi.org/10.48550/arxiv.2509.02108","title":"DivMerge: A divergence-based model merging method for multi-tasking","display_name":"DivMerge: A divergence-based model merging method for multi-tasking","publication_year":2025,"publication_date":"2025-09-02","ids":{"openalex":"https://openalex.org/W4416707750","doi":"https://doi.org/10.48550/arxiv.2509.02108"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2509.02108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.02108","pdf_url":"https://arxiv.org/pdf/2509.02108","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2509.02108","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120566868","display_name":"Brahim Touayouch","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Touayouch, Brahim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027494462","display_name":"Lo\u00efc Fosse","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fosse, Lo\u00efc","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111987611","display_name":"G\u00e9raldine Damnati","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Damnati, G\u00e9raldine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5120521171","display_name":"Gw\u00e9nol\u00e9 Lecorv\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lecorv\u00e9, Gw\u00e9nol\u00e9","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.5336999893188477,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.5336999893188477,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.1445000022649765,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.06620000302791595,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/task","display_name":"Task (project management)","score":0.7315000295639038},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6513000130653381},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.38190001249313354},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.34040001034736633},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3019999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7700999975204468},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7315000295639038},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6513000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5727999806404114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5264999866485596},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.38190001249313354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3808000087738037},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.34040001034736633},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2509.02108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.02108","pdf_url":"https://arxiv.org/pdf/2509.02108","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2509.02108","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2509.02108","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":"pmh:oai:arXiv.org:2509.02108","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2509.02108","pdf_url":"https://arxiv.org/pdf/2509.02108","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"Multi-task":[0],"learning":[1],"(MTL)":[2],"is":[3,36],"often":[4],"achieved":[5],"by":[6],"merging":[7,26,76],"datasets":[8],"before":[9],"fine-tuning,":[10],"but":[11],"the":[12,42,75,96],"growing":[13],"availability":[14],"of":[15,44,98],"fine-tuned":[16],"models":[17,53],"has":[18],"led":[19],"to":[20,73],"new":[21],"approaches":[22],"such":[23],"as":[24,41,95],"model":[25],"via":[27],"task":[28,37,86],"arithmetic.":[29],"A":[30],"major":[31],"challenge":[32],"in":[33],"this":[34],"setting":[35],"interference,":[38],"which":[39],"worsens":[40],"number":[43,97],"tasks":[45,57,99],"increases.":[46],"We":[47],"propose":[48],"a":[49,59],"method":[50],"that":[51],"merges":[52],"trained":[54],"on":[55],"different":[56],"into":[58],"single":[60],"model,":[61],"maintaining":[62],"strong":[63],"performance":[64],"across":[65],"all":[66],"tasks.":[67],"Our":[68],"approach":[69,92],"leverages":[70],"Jensen-Shannon":[71],"divergence":[72],"guide":[74],"process":[77],"without":[78],"requiring":[79],"additional":[80],"labelled":[81],"data,":[82],"and":[83,101],"automatically":[84],"balances":[85],"importance.":[87],"Unlike":[88],"existing":[89],"methods,":[90],"our":[91],"remains":[93],"robust":[94],"grows":[100],"consistently":[102],"outperforms":[103],"prior":[104],"work.":[105]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}