{"id":"https://openalex.org/W7164896449","doi":"https://doi.org/10.48550/arxiv.2606.15080","title":"AdaMame: A Training Recipe for Adaptive Multilingual Reasoning","display_name":"AdaMame: A Training Recipe for Adaptive Multilingual Reasoning","publication_year":2026,"publication_date":"2026-06-13","ids":{"openalex":"https://openalex.org/W7164896449","doi":"https://doi.org/10.48550/arxiv.2606.15080"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.15080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15080","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.15080","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138734603","display_name":"Dayeon Ki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ki, Dayeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138728330","display_name":"Kevin Duh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duh, Kevin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138749189","display_name":"Marine Carpuat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carpuat, Marine","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.1981000006198883,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.1981000006198883,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.18539999425411224,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10028","display_name":"Topic Modeling","score":0.15620000660419464,"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/fidelity","display_name":"Fidelity","score":0.5462999939918518},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5235999822616577},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4724000096321106},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4422999918460846},{"id":"https://openalex.org/keywords/reasoning-system","display_name":"Reasoning system","score":0.4068000018596649},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.37310001254081726},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.36880001425743103},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.3671000003814697}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083000183105469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5544000267982483},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5462999939918518},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5235999822616577},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5029000043869019},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.37310001254081726},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C2780035574","wikidata":"https://www.wikidata.org/wiki/Q30081","display_name":"Multilingualism","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C94922259","wikidata":"https://www.wikidata.org/wiki/Q33215","display_name":"Constructed language","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C36964233","wikidata":"https://www.wikidata.org/wiki/Q7920942","display_name":"Verbal reasoning","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.27869999408721924},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.15080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15080","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.15080","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15080","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.44619572162628174,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"Large":[1],"Reasoning":[2],"Models":[3],"(LRMs)":[4],"show":[5],"strong":[6],"performance":[7,156],"in":[8,15,45,118,140],"English,":[9],"they":[10],"often":[11],"fail":[12],"to":[13,37,77,97,131],"reason":[14],"the":[16,19,38,74,78,103,129,141,169],"language":[17,25,34,76,80,160],"of":[18,112],"query,":[20],"a":[21,32,59,120],"phenomenon":[22],"known":[23],"as":[24],"collapse.":[26],"Existing":[27],"RL-based":[28],"fixes":[29],"typically":[30],"add":[31],"binary":[33],"fidelity":[35],"reward":[36],"accuracy":[39],"objective,":[40],"yet":[41],"still":[42],"incur":[43],"trade-off":[44],"accuracy,":[46,159],"mid-trace":[47],"code-switching,":[48],"and":[49,150,162],"excessive":[50],"token":[51,163],"usage.":[52],"In":[53,102],"this":[54],"work,":[55],"we":[56,107],"propose":[57],"AdaMame,":[58],"two-stage":[60],"training":[61],"recipe":[62],"for":[63],"multilingual":[64,99],"mathematical":[65],"reasoning":[66,75,92,100,135,139,158],"that":[67],"addresses":[68],"these":[69],"limitations":[70],"by":[71],"adaptively":[72],"aligning":[73],"query":[79,142],"without":[81],"compromising":[82],"accuracy.":[83],"The":[84],"first":[85,132],"SFT":[86],"stage":[87],"fine-tunes":[88],"on":[89,172],"naturally":[90],"occurring":[91],"traces":[93],"across":[94,145,157],"five":[95],"languages":[96,136],"establish":[98],"capability.":[101],"subsequent":[104],"RL":[105],"stage,":[106],"introduce":[108],"AdaMame-GRPO,":[109],"an":[110],"adaptation":[111],"Group":[113],"Relative":[114],"Policy":[115],"Optimization":[116],"(GRPO)":[117],"which":[119],"query-conditioned":[121],"alignment":[122],"factor":[123],"grows":[124],"progressively":[125],"during":[126],"training,":[127],"guiding":[128],"model":[130],"explore":[133],"diverse":[134],"before":[137],"exploiting":[138],"language.":[143],"Evaluated":[144],"two":[146,148],"benchmarks,":[147],"LRMs,":[149],"12":[151],"languages,":[152],"AdaMame-GRPO":[153],"achieves":[154],"Pareto-optimal":[155],"fidelity,":[161],"efficiency":[164],"over":[165],"all":[166],"baselines,":[167],"with":[168],"strongest":[170],"gains":[171],"out-of-domain,":[173],"lower-resource":[174],"languages.":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}