{"id":"https://openalex.org/W7159601082","doi":"https://doi.org/10.48550/arxiv.2604.27677","title":"PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models","display_name":"PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159601082","doi":"https://doi.org/10.48550/arxiv.2604.27677"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27677","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27677","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.27677","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134955083","display_name":"Haocheng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huang, Haocheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134985434","display_name":"Yuchen Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134990643","display_name":"Weisong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Weisong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046057883","display_name":"Peizhuo Lv","orcid":"https://orcid.org/0000-0002-2671-4314"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Peizhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134977800","display_name":"Yuan Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134953000","display_name":"Chunrong Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Chunrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134984677","display_name":"Yang Liu (4829)","orcid":"https://orcid.org/0009-0002-7882-4635"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134938789","display_name":"Xiaofang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiaofang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5134955083"],"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":0.4277999997138977,"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":0.4277999997138977,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.11999999731779099,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.10830000042915344,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.9307000041007996},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.7592999935150146},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7001000046730042},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6597999930381775},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3912000060081482},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3434999883174896},{"id":"https://openalex.org/keywords/copy-protection","display_name":"Copy protection","score":0.3434000015258789}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.9307000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7804999947547913},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.7592999935150146},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7001000046730042},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6597999930381775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4921000003814697},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3912000060081482},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3801000118255615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.352400004863739},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C2780581891","wikidata":"https://www.wikidata.org/wiki/Q15738686","display_name":"Copy protection","level":4,"score":0.3434000015258789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2639999985694885},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27677","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27677","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.27677","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27677","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":"article"},"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":{"Constructing":[0],"and":[1,48,54,97,124,180,196,218,242],"curating":[2],"high-quality":[3],"code":[4,68,85,92,240],"datasets":[5,16,241],"requires":[6],"significant":[7],"resources,":[8],"making":[9,145],"them":[10],"valuable":[11],"intellectual":[12,237],"property.":[13],"Unfortunately,":[14],"these":[15],"currently":[17],"face":[18],"severe":[19],"risks":[20],"of":[21,74,91,109,142,239],"unauthorized":[22],"use.":[23],"Although":[24],"digital":[25,228],"watermarking":[26,65,127,229],"offers":[27,243],"a":[28,63,79,114,166,175,181,226],"post":[29],"hoc":[30],"mechanism":[31],"for":[32,67,103,235,246],"copyright":[33],"authentication,":[34],"existing":[35],"methods":[36,204],"are":[37],"predominantly":[38],"based":[39,137],"on":[40,138,189],"the":[41,72,89,107,110,120,139,143,236],"co-occurrence":[42,122],"pattern,":[43,123],"which":[44],"is":[45,49],"not":[46],"robust":[47,64],"susceptible":[50],"to":[51,87,118,161],"watermark":[52,75,95,154,202],"detection":[53,203],"removal":[55],"attacks.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"propose":[61],"PuzzleMark,":[62],"method":[66],"datasets.":[69],"To":[70,105],"reduce":[71],"risk":[73],"exposure,":[76],"PuzzleMark":[77,112,133,156,173,207,231],"introduces":[78],"carrier":[80],"selection":[81],"strategy":[82],"that":[83,172,206],"leverages":[84],"complexity":[86],"evaluate":[88],"suitability":[90,102],"snippets":[93],"as":[94],"carriers,":[96],"selects":[98],"those":[99],"with":[100,186,211],"high":[101],"watermarking.":[104],"enhance":[106],"robustness":[108],"watermark,":[111],"proposes":[113],"novel":[115],"concatenation":[116],"pattern":[117],"replace":[119],"traditional":[121],"implements":[125],"two":[126],"strategies":[128],"through":[129],"variable":[130],"name":[131],"concatenation.":[132],"adaptively":[134],"embeds":[135],"watermarks":[136],"inherent":[140],"characteristics":[141],"code,":[144],"it":[146],"more":[147],"stealthy":[148],"while":[149],"maintaining":[150],"design":[151],"simplicity.":[152],"For":[153],"verification,":[155],"employs":[157],"Fisher's":[158],"exact":[159],"test":[160],"verify":[162],"suspicious":[163,214],"models":[164],"under":[165],"black-box":[167],"setting.":[168],"Experimental":[169],"results":[170],"demonstrate":[171],"achieves":[174],"100%":[176],"verification":[177],"success":[178],"rate":[179,215],"0%":[182],"false":[183],"positive":[184],"rate,":[185],"negligible":[187],"impact":[188],"model":[190],"performance.":[191],"Both":[192],"our":[193,197],"human":[194],"study":[195],"evaluation":[198],"using":[199],"four":[200],"state-of-the-art":[201],"show":[205],"exhibits":[208],"strong":[209,233],"imperceptibility,":[210],"an":[212,219],"average":[213,220],"$\\leq$":[216,222],"0.24":[217],"recall":[221],"30.41%,":[223],"respectively.":[224],"As":[225],"practical":[227],"method,":[230],"provides":[232],"protection":[234],"property":[238],"new":[244],"insights":[245],"future":[247],"research.":[248]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-05-02T00:00:00"}