{"id":"https://openalex.org/W7154314699","doi":"https://doi.org/10.48550/arxiv.2604.11546","title":"RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience","display_name":"RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7154314699","doi":"https://doi.org/10.48550/arxiv.2604.11546"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.11546","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11546","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.11546","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133618453","display_name":"Hanbo Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Hanbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133574597","display_name":"Xuan Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Xuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133597666","display_name":"Yiran Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yiran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133608745","display_name":"Hao Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083787469","display_name":"Shiyu Liang","orcid":"https://orcid.org/0009-0003-2917-2033"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Shiyu","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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5206999778747559,"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":0.5206999778747559,"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":0.10189999639987946,"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":0.041999999433755875,"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":0.7444999814033508},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6261000037193298},{"id":"https://openalex.org/keywords/spoofing-attack","display_name":"Spoofing attack","score":0.616100013256073},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.5336999893188477},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.4156000018119812},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3887999951839447},{"id":"https://openalex.org/keywords/paraphrase","display_name":"Paraphrase","score":0.3346000015735626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473999857902527},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.7444999814033508},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6261000037193298},{"id":"https://openalex.org/C167900197","wikidata":"https://www.wikidata.org/wiki/Q11081100","display_name":"Spoofing attack","level":2,"score":0.616100013256073},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.612500011920929},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4205000102519989},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.4156000018119812},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C2780922921","wikidata":"https://www.wikidata.org/wiki/Q255189","display_name":"Paraphrase","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C527821871","wikidata":"https://www.wikidata.org/wiki/Q228502","display_name":"Access control","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30079999566078186},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2547999918460846},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.11546","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11546","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.11546","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11546","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"model":[2,118],"(LLM)":[3],"watermarking":[4,107,155],"has":[5],"emerged":[6],"as":[7],"a":[8,54,60,88,116,121,158],"promising":[9],"approach":[10],"for":[11,167],"detecting":[12],"and":[13,33,102,162],"attributing":[14],"AI-generated":[15],"text,":[16],"yet":[17],"its":[18],"robustness":[19],"to":[20,36,105,119,142],"black-box":[21,91],"spoofing":[22,51,92,150],"remains":[23],"insufficiently":[24],"evaluated.":[25],"Existing":[26],"evaluation":[27,160],"methods":[28],"often":[29],"demand":[30],"extensive":[31],"datasets":[32],"white-box":[34],"access":[35,104],"algorithmic":[37],"internals,":[38],"limiting":[39],"their":[40],"practical":[41],"applicability.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,85],"study":[47],"watermark":[48],"resilience":[49],"against":[50],"fundamentally":[52],"from":[53],"distributional":[55],"perspective.":[56],"We":[57],"first":[58],"establish":[59],"\\textit{local":[61],"capacity":[62],"bottleneck},":[63],"which":[64],"theoretically":[65],"characterizes":[66],"the":[67,106,134,148,164],"probability":[68],"mass":[69],"that":[70,94],"can":[71],"be":[72],"reallocated":[73],"under":[74],"KL-bounded":[75],"local":[76],"updates":[77],"while":[78],"preserving":[79],"semantic":[80,128],"fidelity.":[81],"Building":[82],"on":[83,130,140],"this,":[84],"propose":[86],"RLSpoofer,":[87],"reinforcement":[89],"learning-based":[90],"attack":[93],"requires":[95],"only":[96],"100":[97],"human-watermarked":[98],"paraphrase":[99],"training":[100],"pairs":[101],"zero":[103],"internals":[108],"or":[109],"detectors.":[110],"Despite":[111],"weak":[112],"supervision,":[113],"it":[114],"empowers":[115],"4B":[117],"achieve":[120],"62.0\\%":[122],"spoof":[123],"success":[124],"rate":[125],"with":[126],"minimal":[127],"shift":[129],"PF-marked":[131],"texts,":[132],"dwarfing":[133],"6\\%":[135],"of":[136,152],"baseline":[137],"models":[138],"trained":[139],"up":[141],"10,000":[143],"samples.":[144],"Our":[145],"findings":[146],"expose":[147],"fragile":[149],"resistance":[151],"current":[153],"LLM":[154],"paradigms,":[156],"providing":[157],"lightweight":[159],"framework":[161],"stressing":[163],"urgent":[165],"need":[166],"more":[168],"robust":[169],"schemes.":[170]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}
