{"id":"https://openalex.org/W7138410754","doi":"https://doi.org/10.48550/arxiv.2603.15004","title":"TriFusion-LLM: Prior-Guided Multimodal Fusion with LLM Arbitration for Fine-grained Code Clone Detection","display_name":"TriFusion-LLM: Prior-Guided Multimodal Fusion with LLM Arbitration for Fine-grained Code Clone Detection","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7138410754","doi":"https://doi.org/10.48550/arxiv.2603.15004"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.15004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15004","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.15004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129692176","display_name":"Mengdi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Mengdi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027727911","display_name":"Yuming Liu","orcid":"https://orcid.org/0000-0002-7995-0847"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129653950","display_name":"He Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, He","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129643837","display_name":"Zifeng Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zifeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129690092","display_name":"Yuqing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yuqing","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5129692176"],"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/T10260","display_name":"Software Engineering Research","score":0.7885000109672546,"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"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.7885000109672546,"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"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.13510000705718994,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.016300000250339508,"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/code","display_name":"Code (set theory)","score":0.4778999984264374},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.4571000039577484},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4528999924659729},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4357999861240387},{"id":"https://openalex.org/keywords/clone","display_name":"clone (Java method)","score":0.40149998664855957},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4011000096797943},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.38350000977516174},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.3310999870300293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638000249862671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5498999953269958},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4778999984264374},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.4571000039577484},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.424699991941452},{"id":"https://openalex.org/C81089528","wikidata":"https://www.wikidata.org/wiki/Q5134986","display_name":"clone (Java method)","level":3,"score":0.40149998664855957},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4011000096797943},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C114408938","wikidata":"https://www.wikidata.org/wiki/Q333373","display_name":"Abstract syntax","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.15004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15004","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.15004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15004","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":"article"},"sustainable_development_goals":[{"score":0.5113615393638611,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.4256434440612793,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Code":[0],"clone":[1,28,85],"detection":[2],"(CCD)":[3],"supports":[4],"software":[5],"maintenance,":[6],"refactoring,":[7],"and":[8,30,62,76,156],"security":[9],"analysis.":[10],"Although":[11],"pre-trained":[12],"models":[13],"capture":[14],"code":[15],"semantics,":[16],"most":[17],"work":[18],"reduces":[19],"CCD":[20,155],"to":[21,103,118],"binary":[22],"classification,":[23],"overlooking":[24],"the":[25,31,93,110],"heterogeneity":[26],"of":[27,135],"types":[29,86],"seven":[32],"fine-grained":[33,84,154],"categories":[34],"in":[35],"BigCloneBench.":[36],"We":[37],"present":[38],"Full":[39,79,97,146],"Model,":[40],"a":[41,69,116,123,158],"multimodal":[42],"fusion":[43],"framework":[44],"that":[45,108],"jointly":[46],"integrates":[47],"heuristic":[48],"similarity":[49],"priors":[50],"from":[51,57,66,101],"classical":[52],"machine":[53],"learning,":[54],"structural":[55],"signals":[56],"abstract":[58],"syntax":[59],"trees":[60],"(ASTs),":[61],"deep":[63],"semantic":[64,77],"embeddings":[65],"CodeBERT":[67],"into":[68],"single":[70],"predictor.":[71],"By":[72],"fusing":[73],"structural,":[74],"statistical,":[75],"representations,":[78],"Model":[80,98,147],"improves":[81],"discrimination":[82],"among":[83],"while":[87],"keeping":[88],"inference":[89],"cost":[90],"practical.":[91],"On":[92],"seven-class":[94],"BigCloneBench":[95],"benchmark,":[96],"raises":[99],"Macro-F1":[100,143],"0.695":[102],"0.875.":[104],"Ablation":[105],"studies":[106],"show":[107],"using":[109],"primary":[111],"model's":[112],"probability":[113],"distribution":[114],"as":[115],"prior":[117],"guide":[119],"selective":[120],"arbitration":[121],"by":[122],"large":[124],"language":[125],"model":[126],"(LLM)":[127],"substantially":[128],"outperforms":[129],"blind":[130],"reclassification;":[131],"arbitrating":[132],"only":[133],"~0.2%":[134],"high-uncertainty":[136],"samples":[137],"yields":[138],"an":[139,149],"additional":[140],"0.3":[141],"absolute":[142],"gain.":[144],"Overall,":[145],"achieves":[148],"effective":[150],"performance-cost":[151],"trade-off":[152],"for":[153,161],"offers":[157],"practical":[159],"solution":[160],"large-scale":[162],"industrial":[163],"deployment.":[164]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}
