{"id":"https://openalex.org/W7128642752","doi":"https://doi.org/10.48550/arxiv.2602.09689","title":"Model soups need only one ingredient","display_name":"Model soups need only one ingredient","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128642752","doi":"https://doi.org/10.48550/arxiv.2602.09689"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.09689","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/A5114601785","display_name":"Alireza Abdollahpoorrostam","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abdollahpoorrostam, Alireza","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125652460","display_name":"Nikolaos Dimitriadis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dimitriadis, Nikolaos","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094246343","display_name":"Adam Hazimeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hazimeh, Adam","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Frossard, Pascal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frossard, Pascal","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114601785"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3407000005245209,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3407000005245209,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.3149999976158142,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0786999985575676,"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/robustness","display_name":"Robustness (evolution)","score":0.733299970626831},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.580299973487854},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4754999876022339},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.46480000019073486},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.4269999861717224},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.39739999175071716}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.733299970626831},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.580299973487854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5547000169754028},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4754999876022339},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46380001306533813},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.39739999175071716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35920000076293945},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3278000056743622},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.31700000166893005},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C2780589914","wikidata":"https://www.wikidata.org/wiki/Q10675206","display_name":"Ingredient","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.09689","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.2602.09689","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.09689","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.2602.09689","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fine-tuning":[0],"large":[1],"pre-trained":[2],"models":[3,144,160],"on":[4,142,146,157,162],"a":[5,63,71,77,174],"target":[6],"distribution":[7,152],"often":[8],"improves":[9],"in-distribution":[10],"(ID)":[11],"accuracy,":[12],"but":[13,42,107],"at":[14],"the":[15,25,48,133,139],"cost":[16],"of":[17,52,54,138,184],"out-of-distribution":[18],"(OOD)":[19],"robustness":[20],"as":[21,32,154,156],"representations":[22],"specialize":[23],"to":[24,87,122,179],"fine-tuning":[26],"data.":[27],"Weight-space":[28],"ensembling":[29],"methods,":[30,181],"such":[31],"Model":[33],"Soups,":[34],"mitigate":[35],"this":[36,58,170],"effect":[37],"by":[38],"averaging":[39],"multiple":[40],"checkpoints,":[41],"they":[43],"are":[44],"computationally":[45],"prohibitive,":[46],"requiring":[47],"training":[49],"and":[50,91,101,135,148,165,176],"storage":[51],"dozens":[53],"fine-tuned":[55,145],"models.":[56],"In":[57],"paper,":[59],"we":[60],"introduce":[61,105],"MonoSoup,":[62],"simple,":[64],"data-free,":[65],"hyperparameter-free,":[66],"post-hoc":[67],"method":[68,81],"that":[69,97,104,130,169],"achieves":[70],"strong":[72],"ID-OOD":[73],"balance":[74],"using":[75],"only":[76],"single":[78],"checkpoint.":[79],"Our":[80],"applies":[82],"Singular":[83],"Value":[84],"Decomposition":[85],"(SVD)":[86],"each":[88],"layer's":[89],"update":[90],"decomposes":[92],"it":[93],"into":[94],"high-energy":[95],"directions":[96,103],"capture":[98],"task-specific":[99],"adaptation":[100],"low-energy":[102],"noise":[106],"may":[108],"still":[109],"encode":[110],"residual":[111],"signals":[112],"useful":[113],"for":[114,132],"robustness.":[115],"MonoSoup":[116],"then":[117],"uses":[118],"entropy-based":[119],"effective":[120,177],"rank":[121],"automatically":[123],"re-weigh":[124],"these":[125],"components":[126],"with":[127],"layer-wise":[128],"coefficients":[129],"account":[131],"spectral":[134],"geometric":[136],"structure":[137],"model.":[140],"Experiments":[141],"CLIP":[143],"ImageNet":[147],"evaluated":[149],"under":[150],"natural":[151],"shifts,":[153],"well":[155],"Qwen":[158],"language":[159],"tested":[161],"mathematical":[163],"reasoning":[164],"multiple-choice":[166],"benchmarks,":[167],"show":[168],"plug-and-play":[171],"approach":[172],"is":[173],"practical":[175],"alternative":[178],"multi-checkpoint":[180],"retaining":[182],"much":[183],"their":[185,188],"benefits":[186],"without":[187],"computational":[189],"overhead.":[190]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-12T00:00:00"}