{"id":"https://openalex.org/W7165662781","doi":"https://doi.org/10.48550/arxiv.2606.21365","title":"LambdaMark: Semantic Audio Watermarking for Robustness and Radioactivity","display_name":"LambdaMark: Semantic Audio Watermarking for Robustness and Radioactivity","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165662781","doi":"https://doi.org/10.48550/arxiv.2606.21365"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21365","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.2606.21365","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139197171","display_name":"Kexin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Kexin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139194750","display_name":"Xiao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074577020","display_name":"Ilya Grishchenko","orcid":"https://orcid.org/0000-0003-4744-7507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Grishchenko, Ilya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049933072","display_name":"David Lie","orcid":"https://orcid.org/0000-0002-2000-6827"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lie, David","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":0.7526999711990356,"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":0.7526999711990356,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.05660000070929527,"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":0.04230000078678131,"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/digital-watermarking","display_name":"Digital watermarking","score":0.9136999845504761},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.8810999989509583},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7908999919891357},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6894000172615051},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5139999985694885},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4007999897003174},{"id":"https://openalex.org/keywords/scrambling","display_name":"Scrambling","score":0.3959999978542328}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.9136999845504761},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.8810999989509583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801800012588501},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7908999919891357},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6894000172615051},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5248000025749207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5213000178337097},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5139999985694885},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C182548165","wikidata":"https://www.wikidata.org/wiki/Q2261483","display_name":"Scrambling","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39259999990463257},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.33820000290870667},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27239999175071716}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21365","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.2606.21365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21365","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7739596366882324}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,41],"generative":[3],"audio":[4,69,122,157],"have":[5,127],"made":[6],"voice":[7,12],"cloning":[8],"increasingly":[9],"effortless,":[10],"enabling":[11],"fraud,":[13],"impersonation,":[14],"and":[15,66,90,130,159,166,173,193,199,231,234,239],"other":[16],"forms":[17],"of":[18,31,185,248],"unauthorized":[19],"use.":[20],"A":[21,57],"common":[22,197,211],"attack":[23],"finetunes":[24],"a":[25,32,48,139,146,160,178],"speech":[26,40],"generation":[27],"model":[28,37,141],"on":[29,244],"recordings":[30],"target":[33],"speaker,":[34],"allowing":[35],"the":[36,101,168,186,216,245],"to":[38,87,94,135,150,162,237],"synthesize":[39],"that":[42,182,205,219],"speaker's":[43],"voice.":[44],"Audio":[45],"watermarking":[46,70,105],"offers":[47],"promising":[49],"defense":[50],"by":[51,115,138],"embedding":[52,116],"detectable":[53],"signals":[54,74],"into":[55,75,120,155],"audio.":[56],"practical":[58],"watermark":[59,118,148,164,218],"must":[60],"satisfy":[61],"two":[62],"key":[63],"properties:":[64],"robustness":[65,195,209],"radioactivity.":[67],"Existing":[68],"methods":[71],"typically":[72],"embed":[73],"low-level":[76],"representations,":[77],"such":[78],"as":[79],"waveforms":[80],"or":[81],"spectrograms,":[82],"which":[83],"makes":[84],"them":[85],"vulnerable":[86],"signal-level":[88],"manipulations":[89],"limits":[91],"their":[92],"transfer":[93],"downstream":[95,140],"models.":[96,251],"We":[97],"introduce":[98],"LambdaMark":[99,111,144,206,213,228],"--":[100],"first":[102],"generic":[103,113],"radioactive":[104],"scheme.":[106],"Unlike":[107],"all":[108,223],"previous":[109],"approaches,":[110],"achieves":[112,207],"radioactivity":[114,233],"multi-bit":[117,152],"information":[119],"semantic":[121,128,156],"latent":[123],"representations.":[124],"Our":[125],"watermarks":[126],"interpretation":[129],"are":[131,175],"thus":[132],"more":[133],"likely":[134],"be":[136],"learned":[137],"through":[142],"finetuning.":[143],"includes":[145],"lightweight":[147],"encoder":[149],"inject":[151],"message-dependent":[153],"perturbations":[154],"representations":[158],"decoder":[161,174],"detect":[163],"presence":[165],"recover":[167],"embedded":[169],"bit":[170],"information.":[171],"Encoder":[172],"trained":[176],"using":[177],"custom":[179],"multi-component":[180],"loss":[181],"preserves":[183],"fidelity":[184],"watermarked":[187],"audio,":[188],"increases":[189],"bit-level":[190],"recovery":[191],"rate,":[192],"improves":[194],"against":[196,222],"distortions":[198,238],"adversarial":[200,240],"removal":[201,225,241],"attempts.":[202],"Experiments":[203],"show":[204],"near-perfect":[208],"under":[210],"distortions.":[212],"is":[214,220],"also":[215],"only":[217],"robust":[221,232,236],"evaluated":[224],"attacks.":[226],"Furthermore,":[227],"exhibits":[229],"general":[230],"remains":[235],"attacks":[242],"even":[243],"generated":[246],"outputs":[247],"those":[249],"finetuned":[250]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}