{"id":"https://openalex.org/W7202137125","doi":"https://doi.org/10.48550/arxiv.2608.06416","title":"WorldMark: A Plug-and-Play World Knowledge Interface for Cross-Host Language Model Watermarking","display_name":"WorldMark: A Plug-and-Play World Knowledge Interface for Cross-Host Language Model Watermarking","publication_year":2026,"publication_date":"2026-08-05","ids":{"openalex":"https://openalex.org/W7202137125","doi":"https://doi.org/10.48550/arxiv.2608.06416"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2608.06416","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06416","pdf_url":"https://arxiv.org/pdf/2608.06416","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.06416","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146426017","display_name":"Song Xiao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023215301","display_name":"Yuqi Yuan","orcid":"https://orcid.org/0009-0001-9630-9074","observed_orcids":["https://orcid.org/0009-0001-9630-9074"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Yuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000136407","display_name":"Yanshuo Zhang","orcid":"https://orcid.org/0000-0002-5349-6447","observed_orcids":["https://orcid.org/0000-0002-5349-6447"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanshuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5146455540","display_name":"Kejun Zhang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Kejun","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":true,"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":0.5536999702453613,"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":0.5536999702453613,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.34940001368522644,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.023600000888109207,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/large-language-models","display_name":"large language models","score":0.6539999842643738},{"id":"https://openalex.org/keywords/memory-graph","display_name":"memory graph","score":0.7990000247955322},{"id":"https://openalex.org/keywords/perplexity","display_name":"perplexity","score":0.38100001215934753}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.7982000112533569},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.7588000297546387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7567999958992004},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.6906999945640564},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.4359999895095825},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4334000051021576},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3935000002384186},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C126831891","wikidata":"https://www.wikidata.org/wiki/Q221673","display_name":"Host (biology)","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3521000146865845},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.3310000002384186},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2718000113964081},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2590000033378601}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.06416","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06416","pdf_url":"https://arxiv.org/pdf/2608.06416","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.06416","doi":"https://doi.org/10.48550/arxiv.2608.06416","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.06416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"pmh:oai:arXiv.org:2608.06416","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.06416","pdf_url":"https://arxiv.org/pdf/2608.06416","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202137125.pdf","grobid_xml":"https://content.openalex.org/works/W7202137125.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Watermarking":[0],"traces":[1],"the":[2,41,83,94,119,123,178],"provenance":[3],"of":[4,30,96],"text":[5],"produced":[6],"by":[7,11],"large":[8],"language":[9],"models":[10],"embedding":[12],"statistically":[13],"detectable":[14],"signals":[15,34],"during":[16],"decoding.":[17],"Existing":[18],"schemes":[19],"fall":[20],"into":[21,86],"logits-based,":[22],"sampling-based,":[23],"entropy-aware,":[24],"and":[25,75,92,110,129,146,173],"adaptive-strength":[26,134],"families,":[27],"yet":[28],"all":[29],"them":[31],"place":[32],"watermark":[33,58,99,156],"according":[35],"to":[36,72],"local":[37,49],"token":[38],"statistics.":[39],"In":[40],"open-ended":[42],"text-generation":[43],"settings":[44],"evaluated":[45],"in":[46,78],"this":[47],"work,":[48],"statistics":[50],"may":[51],"provide":[52],"insufficient":[53],"guidance":[54],"for":[55],"placing":[56],"robust":[57],"signals.":[59],"We":[60],"introduce":[61],"WorldMark,":[62],"a":[63,79,87,97],"plug-and-play":[64],"interface":[65,126],"that":[66,149],"uses":[67],"World":[68],"Knowledge":[69,102],"Memory":[70],"(WKM)":[71],"organize":[73],"semantic":[74],"episodic":[76],"knowledge":[77,85,89],"memory":[80,151],"graph,":[81],"converts":[82],"retrieved":[84],"token-level":[88],"saliency":[90],"score,":[91],"adjusts":[93],"strength":[95],"host":[98,135],"through":[100],"Asymmetric":[101],"Modulation":[103],"(AKM).":[104],"WorldMark":[105,125,165],"requires":[106,166],"no":[107,112,167],"backbone":[108],"retraining":[109],"introduces":[111,174],"additional":[113,168],"detector-side":[114,169],"model":[115,170],"or":[116,171],"parameter.":[117],"On":[118],"primary":[120,179],"C4":[121,145],"evaluation,":[122],"complete":[124],"improves":[127],"clean":[128],"attacked":[130],"detection":[131],"across":[132,154],"three":[133],"variants":[136],"while":[137],"slightly":[138],"reducing":[139],"perplexity.":[140],"Additional":[141],"pilot":[142],"experiments":[143],"on":[144],"OpenGen":[147],"show":[148],"direct":[150],"conditioning":[152],"transfers":[153],"multiple":[155],"families":[157],"but":[158],"can":[159],"be":[160],"unstable":[161],"without":[162],"saliency-aware":[163],"modulation.":[164],"parameter":[172],"negligible":[175],"overhead":[176],"under":[177],"protocol.":[180]},"counts_by_year":[],"updated_date":"2026-09-25T08:18:29.962427","created_date":"2026-08-11T00:00:00"}