{"id":"https://openalex.org/W7160635383","doi":"https://doi.org/10.48550/arxiv.2605.05949","title":"MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System","display_name":"MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160635383","doi":"https://doi.org/10.48550/arxiv.2605.05949"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05949","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.2605.05949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135693115","display_name":"Yuliang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Yuliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019201800","display_name":"Xiang Xu","orcid":"https://orcid.org/0000-0002-8663-9029"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135670747","display_name":"Yao Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126469809","display_name":"Hu Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Hu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135672914","display_name":"Tong Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Tong","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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.12449999898672104,"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"}},"topics":[{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.12449999898672104,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.049800001084804535,"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/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.04969999939203262,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/workflow","display_name":"Workflow","score":0.6600000262260437},{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.5302000045776367},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.48539999127388},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4487000107765198},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.43479999899864197},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.414000004529953}],"concepts":[{"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/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6600000262260437},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.48539999127388},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3756999969482422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3221000134944916},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.31060001254081726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2946000099182129},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05949","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.2605.05949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05949","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Algorithmic":[0],"problem":[1,81,126],"solving":[2,82,98],"serves":[3],"as":[4,16,38],"a":[5,20,66,75,131,161,169],"rigorous":[6],"testbed":[7],"for":[8,79,241],"evaluating":[9],"structured":[10,25,104],"reasoning":[11,26,195],"in":[12,27,148],"AI":[13],"coding":[14],"systems,":[15],"it":[17,121],"directly":[18],"reflects":[19],"model's":[21],"ability":[22],"to":[23,122,191,214,231],"perform":[24,208],"complex":[28],"scenarios.":[29],"Existing":[30],"approaches":[31],"predominantly":[32],"rely":[33],"on":[34,130,155,172],"model-centric":[35],"strategies,":[36],"such":[37],"architectural":[39],"modifications":[40],"and":[41,47,64,90,108,118,181,203,211],"data":[42,158],"scaling,":[43],"which":[44],"are":[45,61],"costly":[46],"offer":[48],"limited":[49],"interpretability.":[50],"Alternative":[51],"methods":[52],"leveraging":[53],"external":[54],"tools":[55],"or":[56],"prompting":[57],"techniques":[58],"(e.g.,":[59],"chain-of-thought)":[60],"often":[62],"fragmented":[63],"lack":[65],"unified":[67],"framework.":[68],"In":[69,151],"this":[70],"paper,":[71],"we":[72,187],"propose":[73],"MAS-Algorithm,":[74],"systematic":[76],"multi-agent":[77],"workflow":[78],"algorithmic":[80,244],"inspired":[83],"by":[84],"the":[85,96,156,194,198,216,220,236],"practices":[86],"of":[87,146,164,219,229,239],"competitive":[88],"programmers":[89],"algorithm":[91],"engineers.":[92],"Our":[93],"framework":[94],"decomposes":[95],"end-to-end":[97],"process":[99,196],"into":[100],"modular":[101],"stages,":[102],"enabling":[103],"reasoning,":[105],"tool":[106],"integration,":[107],"flexible":[109],"coordination":[110],"among":[111],"agents.":[112],"The":[113],"design":[114],"emphasizes":[115],"both":[116],"rigor":[117],"extensibility,":[119],"allowing":[120],"generalize":[123],"across":[124,137,178],"diverse":[125],"types.":[127],"Experimental":[128],"results":[129,234],"self-constructed":[132],"benchmark":[133],"demonstrate":[134],"consistent":[135,176],"improvements":[136,177,228],"multiple":[138],"Qwen":[139],"series":[140],"models,":[141],"achieving":[142],"an":[143],"average":[144],"gain":[145,171],"6.48%":[147],"acceptance":[149],"rate.":[150],"contrast,":[152],"parameter-efficient":[153],"fine-tuning":[154],"same":[157],"yields":[159],"only":[160],"marginal":[162],"improvement":[163],"0.89%.":[165],"We":[166,206],"further":[167,207],"observe":[168],"4.72%":[170],"LiveCodeBench-Pro,":[173],"along":[174],"with":[175],"additional":[179],"accuracy":[180],"efficiency":[182],"metrics.":[183],"Beyond":[184],"performance":[185],"gains,":[186],"conduct":[188],"comprehensive":[189],"analyses":[190],"better":[192],"understand":[193],"within":[197],"workflow,":[199],"including":[200],"error":[201],"patterns":[202],"cross-scenario":[204],"behaviors.":[205],"customized":[209],"replacement":[210],"ablation":[212],"studies":[213],"explore":[215],"upper":[217],"bound":[218],"framework,":[221],"showing":[222],"that":[223],"individual":[224],"agents":[225],"can":[226],"contribute":[227],"up":[230],"27.7%.":[232],"These":[233],"highlight":[235],"strong":[237],"potential":[238],"MAS-Algorithm":[240],"advancing":[242],"AI-driven":[243],"reasoning.":[245]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}