{"id":"https://openalex.org/W7136607282","doi":"https://doi.org/10.48550/arxiv.2603.12698","title":"EvolveCoder: Evolving Test Cases via Adversarial Verification for Code Reinforcement Learning","display_name":"EvolveCoder: Evolving Test Cases via Adversarial Verification for Code Reinforcement Learning","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7136607282","doi":"https://doi.org/10.48550/arxiv.2603.12698"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12698","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":null,"license_id":null,"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.2603.12698","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129500749","display_name":"Chi Ruan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruan, Chi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129492227","display_name":"Dongfu Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Dongfu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111188853","display_name":"Huaye Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Huaye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129588504","display_name":"Ping Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129502789","display_name":"Wenhu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Wenhu","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5027999877929688,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5027999877929688,"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/T10028","display_name":"Topic Modeling","score":0.1111999973654747,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.10599999874830246,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8406000137329102},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6721000075340271},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6656000018119812},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5511000156402588},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4997999966144562},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.47110000252723694},{"id":"https://openalex.org/keywords/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.40220001339912415}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8406000137329102},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.782800018787384},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6721000075340271},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6656000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5857999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5777999758720398},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5511000156402588},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4997999966144562},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.47110000252723694},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.40220001339912415},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.34150001406669617},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.2856999933719635},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.27399998903274536}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12698","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12698","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":null,"license_id":null,"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":0.6949997544288635}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0,108],"learning":[1,81,109,150],"with":[2,58,101],"verifiable":[3],"rewards":[4],"(RLVR)":[5],"is":[6,21],"a":[7,39,77],"promising":[8],"approach":[9],"for":[10,145],"improving":[11,64,119],"code":[12,152],"generation":[13],"in":[14,29,151],"large":[15],"language":[16],"models,":[17],"but":[18],"its":[19],"effectiveness":[20],"limited":[22],"by":[23,121],"weak":[24],"and":[25,41,67,115,131,147],"static":[26],"verification":[27,43,144],"signals":[28],"existing":[30],"coding":[31,79],"RL":[32],"datasets.":[33],"In":[34],"this":[35,72],"paper,":[36],"we":[37,74],"propose":[38],"solution-conditioned":[40,143],"adversarial":[42,88],"framework":[44],"that":[45,95],"iteratively":[46],"refines":[47],"test":[48,89],"cases":[49],"based":[50],"on":[51,71,110],"the":[52,59,139],"execution":[53],"behaviors":[54],"of":[55,61,87,124,141],"candidate":[56],"solutions,":[57],"goal":[60],"increasing":[62],"difficulty,":[63],"discriminative":[65],"power,":[66],"reducing":[68],"redundancy.":[69],"Based":[70],"framework,":[73],"introduce":[75],"EvolveCoder-22k,":[76],"large-scale":[78],"reinforcement":[80,149],"dataset":[82],"constructed":[83],"through":[84],"multiple":[85],"rounds":[86],"case":[90],"evolution.":[91],"Empirical":[92],"analysis":[93],"shows":[94],"iterative":[96],"refinement":[97],"substantially":[98],"strengthens":[99],"verification,":[100],"pass@1":[102],"decreasing":[103],"from":[104],"43.80":[105],"to":[106],"31.22.":[107],"EvolveCoder-22k":[111],"yields":[112],"stable":[113],"optimization":[114],"consistent":[116],"performance":[117],"gains,":[118],"Qwen3-4B":[120],"an":[122],"average":[123],"4.2":[125],"points":[126],"across":[127],"four":[128],"downstream":[129],"benchmarks":[130],"outperforming":[132],"strong":[133],"4B-scale":[134],"baselines.":[135],"Our":[136],"results":[137],"highlight":[138],"importance":[140],"adversarial,":[142],"effective":[146],"scalable":[148],"generation.":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-17T00:00:00"}