{"id":"https://openalex.org/W7155086021","doi":"https://doi.org/10.48550/arxiv.2604.18473","title":"Train Separately, Merge Together: Modular Post-Training with Mixture-of-Experts","display_name":"Train Separately, Merge Together: Modular Post-Training with Mixture-of-Experts","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155086021","doi":"https://doi.org/10.48550/arxiv.2604.18473"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18473","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18473","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.18473","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134206219","display_name":"Jacob Morrison","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morrison, Jacob","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134158101","display_name":"Sanjay Adhikesaven","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adhikesaven, Sanjay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134096915","display_name":"Akshita Bhagia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhagia, Akshita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134179264","display_name":"Matei Zaharia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zaharia, Matei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134170097","display_name":"Noah A. Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, Noah A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5039158419","display_name":"Sewon Min","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Min, Sewon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T10028","display_name":"Topic Modeling","score":0.46959999203681946,"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/T10028","display_name":"Topic Modeling","score":0.46959999203681946,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.11219999939203262,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.06970000267028809,"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/scalability","display_name":"Scalability","score":0.6622999906539917},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6407999992370605},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.5706999897956848},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.48330000042915344},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.37560001015663147},{"id":"https://openalex.org/keywords/scratch","display_name":"Scratch","score":0.35519999265670776},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.32420000433921814},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3206999897956848}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150999903678894},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6622999906539917},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6407999992370605},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5706999897956848},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42570000886917114},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3578999936580658},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C2775896111","wikidata":"https://www.wikidata.org/wiki/Q642560","display_name":"Router","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C2776303644","wikidata":"https://www.wikidata.org/wiki/Q1020499","display_name":"Interfacing","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C2779104521","wikidata":"https://www.wikidata.org/wiki/Q23058469","display_name":"Contouring","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18473","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18473","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":"doi:10.48550/arxiv.2604.18473","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18473","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4475993514060974}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Extending":[0],"a":[1,56,139,173,184],"fully":[2],"post-trained":[3],"language":[4,192],"model":[5],"with":[6,59,87,101],"new":[7],"domain":[8,39],"capabilities":[9,157],"is":[10,20,183],"fundamentally":[11],"limited":[12],"by":[13,142],"monolithic":[14,188],"training":[15,27,137,160,182],"paradigms:":[16],"retraining":[17,64,189],"from":[18,158],"scratch":[19],"expensive":[21],"and":[22,48,52,70,91,108,167],"scales":[23],"poorly,":[24],"while":[25,162],"continued":[26],"often":[28],"degrades":[29,156],"existing":[30,95],"capabilities.":[31],"We":[32,132],"present":[33],"BAR":[34,81,110],"(Branch-Adapt-Route),":[35],"which":[36],"trains":[37],"independent":[38],"experts,":[40],"each":[41,144],"through":[42],"its":[43],"own":[44],"mid-training,":[45,129],"supervised":[46],"finetuning,":[47],"reinforcement":[49],"learning":[50],"pipeline,":[51],"composes":[53],"them":[54],"via":[55],"Mixture-of-Experts":[57],"architecture":[58],"lightweight":[60],"router":[61],"training.":[62],"Unlike":[63],"approaches":[65],"that":[66,135,151,179],"mix":[67],"all":[68],"domains":[69],"require":[71],"full":[72],"reprocessing":[73],"for":[74,103,190],"any":[75],"update":[76],"(with":[77],"cost":[78,89,166],"scaling":[79,90],"quadratically),":[80],"enables":[82],"updating":[83,170],"individual":[84],"experts":[85,102],"independently":[86],"linear":[88],"no":[92],"degradation":[93],"to":[94,187],"domains.":[96],"At":[97],"the":[98,148,165],"7B":[99],"scale,":[100],"math,":[104],"code,":[105],"tool":[106],"use,":[107],"safety,":[109],"achieves":[111],"an":[112],"overall":[113],"score":[114],"of":[115,169],"49.1":[116],"(averaged":[117],"across":[118],"7":[119],"evaluation":[120],"categories),":[121],"matching":[122],"or":[123,171],"exceeding":[124],"re-training":[125],"baselines":[126],"(47.8":[127],"without":[128],"50.5":[130],"with).":[131],"further":[133],"show":[134],"modular":[136],"provides":[138],"structural":[140],"advantage:":[141],"isolating":[143],"domain,":[145],"it":[146],"avoids":[147],"catastrophic":[149],"forgetting":[150],"occurs":[152],"when":[153],"late-stage":[154],"RL":[155],"earlier":[159],"stages,":[161],"significantly":[163],"reducing":[164],"complexity":[168],"adding":[172],"domain.":[174],"Together,":[175],"these":[176],"results":[177],"suggest":[178],"decoupled,":[180],"expert-based":[181],"scalable":[185],"alternative":[186],"extending":[191],"models.":[193]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-22T00:00:00"}
