{"id":"https://openalex.org/W7162334004","doi":"https://doi.org/10.48550/arxiv.2605.23491","title":"CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test","display_name":"CoSPlay: Cooperative Self-Play at Test-Time with Self-Generated Code and Unit Test","publication_year":2026,"publication_date":"2026-05-22","ids":{"openalex":"https://openalex.org/W7162334004","doi":"https://doi.org/10.48550/arxiv.2605.23491"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.23491","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23491","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.2605.23491","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013742405","display_name":"Zhangyi Hu","orcid":"https://orcid.org/0000-0003-3867-6535"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Zhangyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101896268","display_name":"Chenhui Liu","orcid":"https://orcid.org/0009-0008-1537-3834"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Chenhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136897094","display_name":"Tian Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136946476","display_name":"Jindong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jindong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136944547","display_name":"Yang Yang","orcid":"https://orcid.org/0009-0009-9297-7583"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136915237","display_name":"Jiemin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jiemin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136908355","display_name":"Zining Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Zining","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136941508","display_name":"Menglin Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Menglin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136915512","display_name":"Yutao Yue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yue, Yutao","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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.4950999915599823,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.4950999915599823,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.12680000066757202,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.053700000047683716,"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/executable","display_name":"Executable","score":0.7731000185012817},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6722000241279602},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5561000108718872},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.46219998598098755},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43860000371932983},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43389999866485596},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4189000129699707},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4108000099658966}],"concepts":[{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.7731000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7544999718666077},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6722000241279602},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5561000108718872},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4442000091075897},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C148027188","wikidata":"https://www.wikidata.org/wiki/Q907375","display_name":"Unit testing","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34860000014305115},{"id":"https://openalex.org/C53942775","wikidata":"https://www.wikidata.org/wiki/Q1211721","display_name":"Code coverage","level":3,"score":0.3382999897003174},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27000001072883606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2678999900817871},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.2587999999523163},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2581000030040741},{"id":"https://openalex.org/C122637931","wikidata":"https://www.wikidata.org/wiki/Q118084","display_name":"Unit (ring theory)","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.23491","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23491","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.2605.23491","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.23491","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.547110378742218}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"Reinforcement":[1],"Learning":[2],"with":[3,70,247],"Verifiable":[4],"Rewards":[5],"(RLVR)":[6],"and":[7,57,73,107,118,147,208,238],"Test-Time":[8],"Scaling":[9],"(TTS)":[10],"have":[11],"advanced":[12],"LLM":[13],"code":[14,59,173,264],"generation":[15,265],"through":[16,109],"executable":[17],"verification.":[18],"Yet":[19,61],"Ground-Truth":[20],"Unit":[21],"Tests":[22],"(GT":[23],"UTs)":[24],"remain":[25,162],"a":[26,99,258],"bottleneck:":[27],"SOTA":[28],"RLVR":[29,219],"methods":[30,39,50],"require":[31],"them":[32],"for":[33,262],"costly":[34],"training,":[35],"while":[36,187],"existing":[37,49],"TTS":[38,241],"lose":[40],"competitiveness":[41],"without":[42,81,266],"them.":[43],"This":[44],"motivates":[45],"GT-free":[46,240],"TTS,":[47],"where":[48],"directly":[51],"use":[52],"self-generated":[53],"UTs":[54,63,108],"to":[55,89,124,140,206,213,224],"refine":[56],"select":[58],"candidates.":[60],"such":[62],"are":[64],"often":[65],"noisy":[66],"or":[67,143,149,216],"spuriously":[68],"coupled":[69],"wrong":[71,188],"code,":[72],"UT":[74,127,209],"quality":[75],"in":[76],"turn":[77],"cannot":[78],"be":[79],"validated":[80],"reliable":[82],"code.":[83],"The":[84],"key":[85],"challenge":[86],"is":[87],"therefore":[88],"jointly":[90,104],"improve":[91],"both.":[92],"To":[93],"this":[94],"end,":[95],"we":[96],"present":[97],"CoSPlay,":[98],"GT-free,":[100],"training-free":[101],"framework":[102],"that":[103,197],"improves":[105,201,228],"codes":[106,146,161,181,189],"cooperative":[110],"self-play.":[111],"It":[112,129],"first":[113],"explores":[114],"diverse":[115,236],"solution":[116],"ideas":[117],"identifies":[119],"their":[120],"potential":[121],"failure":[122],"modes":[123],"produce":[125],"discriminative":[126],"ideas.":[128],"then":[130],"uses":[131],"bidirectional":[132],"pass-count":[133],"signals":[134],"from":[135,174,204,211],"the":[136,154,165,171,175,184,218,251],"Code-UT":[137],"execution":[138],"matrix":[139],"iteratively":[141],"prune":[142],"fix":[144],"weak":[145],"refresh":[148],"replace":[150],"unreliable":[151],"UTs,":[152],"letting":[153],"two":[155],"pools":[156],"co-evolve.":[157],"Finally,":[158],"when":[159],"multiple":[160],"tied":[163],"at":[164],"highest":[166],"pass":[167],"count,":[168],"it":[169,226],"picks":[170],"final":[172],"largest":[176],"output-consensus":[177],"cluster,":[178],"since":[179],"correct":[180],"agree":[182],"on":[183,192,199],"same":[185],"inputs":[186],"diverge.":[190],"Experiments":[191],"four":[193],"challenging":[194],"benchmarks":[195],"show":[196],"CoSPlay":[198,232],"Qwen2.5-7B-Instruct":[200],"average":[202],"BoN":[203,229],"22.1%":[205],"33.2%":[207],"accuracy":[210],"14.6%":[212],"78.3%,":[214],"matching":[215],"surpassing":[217],"model":[220],"CURE-7B.":[221],"When":[222],"applied":[223],"CURE-7B,":[225],"further":[227],"by":[230],"5.7%.":[231],"also":[233],"generalizes":[234],"across":[235],"backbones":[237],"outperforms":[239],"baselines":[242],"under":[243],"comparable":[244],"token":[245],"budgets,":[246],"continued":[248],"gains":[249],"as":[250],"budget":[252],"scales":[253],"up.":[254],"These":[255],"results":[256],"suggest":[257],"scalable":[259],"inference":[260],"strategy":[261],"competitive":[263],"any":[267],"GT":[268],"data.":[269]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-26T00:00:00"}