{"id":"https://openalex.org/W7134068792","doi":"https://doi.org/10.48550/arxiv.2603.05310","title":"Latent-Mark: An Audio Watermark Robust to Neural Resynthesis","display_name":"Latent-Mark: An Audio Watermark Robust to Neural Resynthesis","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134068792","doi":"https://doi.org/10.48550/arxiv.2603.05310"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.05310","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124949373","display_name":"Yen-Shan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yen-Shan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128265361","display_name":"Shih-Yu Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Shih-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128273290","display_name":"Ying-Jung Tsou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsou, Ying-Jung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128274675","display_name":"Yi-Cheng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Yi-Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047845215","display_name":"Bing\u2010Yu Chen","orcid":"https://orcid.org/0000-0003-0169-7682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Bing-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111041605","display_name":"Yi Chen","orcid":"https://orcid.org/0009-0008-8661-2855"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yun-Nung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128232917","display_name":"Hung-yi Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Hung-yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128259862","display_name":"Shang-Tse Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shang-Tse","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.5724999904632568,"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"}},"topics":[{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.5724999904632568,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.3249000012874603,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.01489999983459711,"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":0.7649999856948853},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.7063999772071838},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5976999998092651},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4490000009536743},{"id":"https://openalex.org/keywords/audio-signal","display_name":"Audio signal","score":0.4334000051021576},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.37940001487731934},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.3456000089645386},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3319999873638153},{"id":"https://openalex.org/keywords/digital-audio","display_name":"Digital audio","score":0.32670000195503235}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7985000014305115},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.7649999856948853},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.7063999772071838},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5976999998092651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4871000051498413},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.4334000051021576},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.37940001487731934},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C87687168","wikidata":"https://www.wikidata.org/wiki/Q173114","display_name":"Digital audio","level":4,"score":0.32670000195503235},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C127220857","wikidata":"https://www.wikidata.org/wiki/Q2719318","display_name":"Audio signal processing","level":4,"score":0.31290000677108765},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2989000082015991},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.05310","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},{"id":"doi:10.48550/arxiv.2603.05310","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.05310","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.05310","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"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":{"While":[0],"existing":[1],"audio":[2,27,54,88,109],"watermarking":[3,42,55,168],"techniques":[4],"have":[5],"achieved":[6],"strong":[7],"robustness":[8,67],"against":[9,153],"traditional":[10,154],"digital":[11],"signal":[12],"processing":[13],"(DSP)":[14],"attacks,":[15],"they":[16],"remain":[17],"vulnerable":[18],"to":[19,58,68,90,104,111,117,135,146],"neural":[20,26,148],"resynthesis.":[21],"This":[22],"occurs":[23],"because":[24],"modern":[25],"codecs":[28,134],"act":[29],"as":[30],"semantic":[31,60],"filters":[32],"and":[33,177],"discard":[34],"the":[35,51,69,74,77,87,107,129],"imperceptible":[36],"waveform":[37,89,130],"variations":[38],"used":[39],"in":[40,96],"prior":[41],"methods.":[43],"To":[44,114],"address":[45],"this":[46,84],"limitation,":[47],"we":[48,123],"propose":[49],"Latent-Mark,":[50],"first":[52],"zero-bit":[53],"framework":[56],"designed":[57],"survive":[59],"compression.":[61],"Our":[62,161],"key":[63],"insight":[64],"is":[65],"that":[66],"encode-decode":[70],"process":[71],"requires":[72],"embedding":[73],"watermark":[75],"within":[76],"codec's":[78,120],"invariant":[79],"latent":[80,99,138],"space.":[81],"We":[82],"achieve":[83],"by":[85],"optimizing":[86,128],"induce":[91],"a":[92,118],"detectable":[93],"directional":[94],"shift":[95],"its":[97],"encoded":[98],"representation,":[100],"while":[101,157],"constraining":[102],"perturbations":[103],"align":[105],"with":[106],"natural":[108],"manifold":[110],"ensure":[112],"imperceptibility.":[113,160],"prevent":[115],"overfitting":[116],"single":[119],"quantization":[121],"rules,":[122],"introduce":[124],"Cross-Codec":[125],"Optimization,":[126],"jointly":[127],"across":[131,174],"multiple":[132],"surrogate":[133],"target":[136],"shared":[137],"invariants.":[139],"Extensive":[140],"evaluations":[141],"demonstrate":[142],"robust":[143],"zero-shot":[144],"transferability":[145],"unseen":[147],"codecs,":[149],"achieving":[150],"state-of-the-art":[151],"resilience":[152],"DSP":[155],"attacks":[156],"preserving":[158],"perceptual":[159],"work":[162],"inspires":[163],"future":[164],"research":[165],"into":[166],"universal":[167],"frameworks":[169],"capable":[170],"of":[171],"maintaining":[172],"integrity":[173],"increasingly":[175],"complex":[176],"diverse":[178],"generative":[179],"distortions.":[180]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-07T00:00:00"}
