{"id":"https://openalex.org/W4412888151","doi":"https://doi.org/10.18653/v1/2025.findings-acl.739","title":"Low-Entropy Watermark Detection via Bayes\u2019 Rule Derived Detector","display_name":"Low-Entropy Watermark Detection via Bayes\u2019 Rule Derived Detector","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888151","doi":"https://doi.org/10.18653/v1/2025.findings-acl.739"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.739","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.739","pdf_url":"https://aclanthology.org/2025.findings-acl.739.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.739.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113520791","display_name":"Beining Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Beining Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065937069","display_name":"Diqing Su","orcid":"https://orcid.org/0000-0002-5790-8744"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du Su","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100872623","display_name":"Fei Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Sun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101692230","display_name":"Qi Cao","orcid":"https://orcid.org/0000-0003-3243-5693"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Cao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103007496","display_name":"Huawei Shen","orcid":"https://orcid.org/0000-0003-1204-4820"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huawei Shen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5029998682","display_name":"Xueqi Cheng","orcid":"https://orcid.org/0000-0002-5201-8195"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xueqi Cheng","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":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"14330","last_page":"14344"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9922999739646912,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.9764000177383423,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6516422033309937},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.640983521938324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5455429553985596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5335237383842468},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5202180743217468},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4942372143268585},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.46858876943588257},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4484878480434418},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.24095946550369263},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.21198487281799316}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6516422033309937},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.640983521938324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5455429553985596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5335237383842468},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5202180743217468},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4942372143268585},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.46858876943588257},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4484878480434418},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.24095946550369263},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.21198487281799316},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.739","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.739","pdf_url":"https://aclanthology.org/2025.findings-acl.739.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.739","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.739","pdf_url":"https://aclanthology.org/2025.findings-acl.739.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888151.pdf","grobid_xml":"https://content.openalex.org/works/W4412888151.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2369048989","https://openalex.org/W2142488199","https://openalex.org/W2387794751","https://openalex.org/W2367131347","https://openalex.org/W2031031029","https://openalex.org/W4286233224","https://openalex.org/W4312782971","https://openalex.org/W2539870919","https://openalex.org/W2125820283","https://openalex.org/W2417174640"],"abstract_inverted_index":{"Text":[0],"watermarking,":[1],"which":[2,67,107],"modify":[3],"tokens":[4,30,92],"to":[5,17,45,150],"embed":[6],"watermark,":[7],"has":[8],"proven":[9],"effective":[10],"in":[11,31,89,129,156,163],"detecting":[12],"machine-generated":[13],"texts.Yet":[14],"its":[15,136],"application":[16],"low-entropy":[18],"texts":[19,33],"like":[20],"code":[21,164],"and":[22,73,134,142,152,166],"mathematics":[23],"presents":[24],"significant":[25],"challenges.A":[26],"fair":[27],"number":[28,63],"of":[29,50,64,119,126,131],"these":[32],"are":[34,68],"hardly":[35],"modifiable":[36],"without":[37],"changing":[38],"the":[39,48,116,124,160],"intended":[40],"meaning,":[41],"causing":[42],"statistical":[43],"measures":[44],"falsely":[46],"indicate":[47],"absence":[49],"a":[51,61],"watermark.Existing":[52],"research":[53],"addresses":[54],"this":[55,97],"issue":[56],"by":[57,114],"rely":[58],"mainly":[59],"on":[60],"limited":[62],"high-entropy":[65],"tokens,":[66],"considered":[69],"flexible":[70],"for":[71],"modification,":[72],"accurately":[74],"reflecting":[75],"watermarks.However,":[76],"their":[77],"detection":[78,132,157],"accuracy":[79,158],"remains":[80],"suboptimal,":[81],"as":[82],"they":[83],"neglect":[84],"strong":[85],"watermark":[86,109,143],"evidences":[87],"embedded":[88],"low":[90],"entropy":[91],"modified":[93],"through":[94],"watermarking.To":[95],"overcome":[96],"limitation,":[98],"we":[99],"introduce":[100],"Bayes'":[101],"Rule":[102],"derived":[103],"Watermark":[104],"Detector":[105],"(BRWD),":[106],"exploit":[108],"information":[110],"from":[111],"every":[112],"token,":[113],"leveraging":[115],"posterior":[117],"probability":[118],"watermark's":[120],"presence.We":[121],"theoretically":[122],"prove":[123],"optimality":[125],"our":[127,146],"method":[128,147],"terms":[130],"accuracy,":[133],"demonstrate":[135],"superiority":[137],"across":[138],"various":[139],"datasets,":[140],"models,":[141],"injection":[144],"strategies.Notably,":[145],"achieves":[148],"up":[149],"50%":[151],"70%":[153],"relative":[154],"improvements":[155],"over":[159],"best":[161],"baselines":[162],"generation":[165],"math":[167],"problem-solving":[168],"tasks,":[169],"respectively.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}