{"id":"https://openalex.org/W7152533497","doi":"https://doi.org/10.48550/arxiv.2604.06618","title":"PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy","display_name":"PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152533497","doi":"https://doi.org/10.48550/arxiv.2604.06618"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.06618","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06618","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.2604.06618","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009023958","display_name":"Phan The Duy","orcid":"https://orcid.org/0000-0002-5945-3712"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duy, Phan The","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ngo-Khanh, Khoa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ngo-Khanh, Khoa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Quyen, Nguyen Huu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quyen, Nguyen Huu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Pham, Van-Hau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pham, Van-Hau","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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.2784999907016754,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.2784999907016754,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.149399995803833,"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/T12479","display_name":"Web Application Security Vulnerabilities","score":0.11230000108480453,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/exploit","display_name":"Exploit","score":0.9696999788284302},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6274999976158142},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5551000237464905},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5164999961853027},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.4293999969959259}],"concepts":[{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.9696999788284302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8133999705314636},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6274999976158142},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5551000237464905},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5164999961853027},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3912999927997589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.351500004529953},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2651999890804291}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.06618","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06618","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.2604.06618","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06618","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.43369030952453613}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"recent":[1],"approaches":[2],"leverage":[3],"large":[4],"language":[5],"models":[6],"(LLMs)":[7],"and":[8,35,59,68,88,99,123,154,166,178,194],"multi-agent":[9,141],"pipelines":[10],"to":[11,184,203],"automatically":[12],"generate":[13],"proof-of-concept":[14],"(PoC)":[15],"exploits":[16,83],"from":[17,24],"vulnerability":[18,97,200],"reports,":[19],"existing":[20],"systems":[21],"often":[22],"suffer":[23],"two":[25],"fundamental":[26],"limitations:":[27],"unreliable":[28],"validation":[29,67,193],"based":[30],"on":[31,163],"surface-level":[32],"execution":[33],"signals":[34],"high":[36],"operational":[37],"cost":[38,182,220],"caused":[39],"by":[40,84,176],"extensive":[41],"trial-and-error":[42],"during":[43],"exploit":[44,127,152,180,225],"generation.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,107],"present":[50],"PoC-Adapt,":[51],"an":[52,110,117],"end-to-end":[53],"framework":[54],"for":[55,146],"automated":[56,199],"PoC":[57,212],"generation":[58,181],"verification,":[60],"architected":[61],"upon":[62],"a":[63,78,140,219],"foundation":[64],"semantic":[65,121,155,192],"runtime":[66],"adaptive":[69],"policy":[70,119],"learning.":[71],"At":[72],"the":[73,126,164,189,204],"core":[74],"of":[75,191,214,221],"PoC-Adapt":[76,136,171,208],"is":[77,137],"Semantic":[79],"Oracle":[80],"that":[81,115,170],"validates":[82],"comparing":[85],"structured":[86,159],"pre-":[87],"post-execution":[89],"system":[90,142],"states,":[91],"enabling":[92],"reliable":[93],"distinction":[94],"between":[95],"true":[96],"exploitation":[98,118],"incidental":[100],"behavioral":[101],"changes.":[102],"To":[103],"reduce":[104],"exploration":[105],"cost,":[106],"further":[108],"introduce":[109],"Adaptive":[111],"Policy":[112],"Learning":[113],"mechanism":[114],"learns":[116],"over":[120],"states":[122],"actions,":[124],"guiding":[125],"agent":[128],"toward":[129],"effective":[130],"strategies":[131],"with":[132],"fewer":[133],"failed":[134],"attempts.":[135],"implemented":[138],"as":[139],"comprising":[143],"specialized":[144],"agents":[145],"root":[147],"cause":[148],"analysis,":[149],"environment":[150],"building,":[151],"generation,":[153],"validation,":[156],"coordinated":[157],"through":[158],"feedback":[160],"loops.":[161],"Experimenting":[162],"CWE-Bench-Java":[165],"PrimeVul":[167],"benchmarks":[168],"shows":[169],"significantly":[172],"improves":[173],"verification":[174],"reliability":[175],"25%":[177],"reduces":[179],"compared":[183],"prior":[185],"LLM-based":[186],"systems,":[187],"highlighting":[188],"importance":[190],"learned":[195],"action":[196],"policies":[197],"in":[198],"reproduction.":[201],"Applied":[202],"latest":[205],"CVE":[206],"corpus,":[207],"confirmed":[209],"12":[210],"verified":[211],"out":[213],"80":[215],"reproduce":[216],"attempts":[217],"at":[218],"$0.42":[222],"per":[223],"generated":[224]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-10T00:00:00"}
