{"id":"https://openalex.org/W7162690847","doi":"https://doi.org/10.48550/arxiv.2605.28456","title":"Diffusion Large Language Models for Visual Speech Recognition","display_name":"Diffusion Large Language Models for Visual Speech Recognition","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162690847","doi":"https://doi.org/10.48550/arxiv.2605.28456"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28456","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28456","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.28456","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089479205","display_name":"Jeong Hun Yeo","orcid":"https://orcid.org/0009-0002-8135-6625"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeo, Jeong Hun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137210588","display_name":"Chae Won Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Chae Won","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137241077","display_name":"Hyeongseop Rha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rha, Hyeongseop","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137249025","display_name":"Yong Man Ro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ro, Yong Man","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10860","display_name":"Speech and Audio Processing","score":0.8012999892234802,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.8012999892234802,"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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.1031000018119812,"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/T11448","display_name":"Face recognition and analysis","score":0.02850000001490116,"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/decodes","display_name":"Decodes","score":0.798799991607666},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6445000171661377},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6229000091552734},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5389000177383423},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4862000048160553},{"id":"https://openalex.org/keywords/coarticulation","display_name":"Coarticulation","score":0.4449999928474426},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4180999994277954},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.4169999957084656},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.798799991607666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7867000102996826},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6906999945640564},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6445000171661377},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6229000091552734},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5389000177383423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5277000069618225},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C130727458","wikidata":"https://www.wikidata.org/wiki/Q1639109","display_name":"Coarticulation","level":3,"score":0.4449999928474426},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.39489999413490295},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.3301999866962433},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29249998927116394},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2782999873161316},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2728999853134155},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28456","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28456","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":"doi:10.48550/arxiv.2605.28456","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28456","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6623721122741699}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"Visual":[1],"Speech":[2],"Recognition":[3],"(VSR)":[4],"systems":[5],"commonly":[6],"rely":[7],"on":[8,17,159],"left-to-right":[9],"autoregressive":[10],"decoding,":[11,101,127],"which":[12,102,128],"can":[13,115],"force":[14],"premature":[15],"decisions":[16],"visually":[18],"ambiguous":[19,71],"tokens":[20,65],"before":[21],"sufficient":[22],"context":[23,68],"is":[24],"available.":[25],"We":[26,93],"propose":[27],"DLLM-VSR,":[28],"to":[29,69,76,105,132],"the":[30,35,63,106],"best":[31],"of":[32,157],"our":[33],"knowledge,":[34],"first":[36],"Diffusion":[37],"Large":[38],"Language":[39],"Model":[40],"(DLLM)-based":[41],"VSR":[42],"framework,":[43],"formulating":[44],"transcription":[45],"as":[46,66],"iterative":[47],"masked":[48],"denoising":[49],"with":[50,99],"flexible-order":[51],"decoding.":[52],"With":[53],"confidence-based":[54],"unmasking,":[55],"DLLM-VSR":[56],"commits":[57],"high-confidence":[58],"positions":[59],"early":[60],"and":[61,141,147],"uses":[62,129],"committed":[64],"bidirectional":[67],"refine":[70],"ones.":[72],"To":[73,119],"adapt":[74],"DLLMs":[75],"VSR,":[77],"we":[78,123],"introduce":[79],"a":[80,96,154],"two-stage":[81],"masked-denoising":[82],"training":[83,165],"strategy":[84],"that":[85,111],"separates":[86],"visual-to-text":[87],"content":[88],"alignment":[89],"from":[90],"length":[91,145],"modeling.":[92],"further":[94],"observe":[95],"performance":[97],"gap":[98],"oracle-length":[100],"assumes":[103],"access":[104],"true":[107],"transcript":[108],"length,":[109],"indicating":[110],"reducing":[112],"target-length":[113],"uncertainty":[114],"improve":[116],"DLLM-based":[117],"VSR.":[118],"reduce":[120],"this":[121],"gap,":[122],"develop":[124],"length-guided":[125],"candidate":[126],"video":[130],"duration":[131],"construct":[133],"plausible":[134],"transcript-length":[135],"hypotheses,":[136,140],"decodes":[137],"under":[138],"multiple":[139],"reranks":[142],"candidates":[143],"using":[144,161],"plausibility":[146],"decoding":[148],"confidence.":[149],"The":[150],"proposed":[151],"method":[152],"achieves":[153],"state-of-the-art":[155],"WER":[156],"19.5\\%":[158],"LRS3":[160],"only":[162],"its":[163],"labeled":[164],"data.":[166]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-29T00:00:00"}
