{"id":"https://openalex.org/W7126042196","doi":"https://doi.org/10.48550/arxiv.2601.20791","title":"FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Models","display_name":"FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Models","publication_year":2026,"publication_date":"2026-01-28","ids":{"openalex":"https://openalex.org/W7126042196","doi":"https://doi.org/10.48550/arxiv.2601.20791"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2601.20791","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/A5043645488","display_name":"Haonan Zhong","orcid":"https://orcid.org/0009-0009-5849-3489"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhong, Haonan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124293280","display_name":"Wei Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124217095","display_name":"Tingxu Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Tingxu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124288998","display_name":"Maurice Pagnucco","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pagnucco, Maurice","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123851584","display_name":"Jingling Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Jingling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124229007","display_name":"Yang Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043645488"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.703499972820282,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.703499972820282,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0681999996304512,"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/T11448","display_name":"Face recognition and analysis","score":0.026900000870227814,"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/debiasing","display_name":"Debiasing","score":0.9950000047683716},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5069000124931335},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.37369999289512634},{"id":"https://openalex.org/keywords/selection-bias","display_name":"Selection bias","score":0.3630000054836273},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.31940001249313354},{"id":"https://openalex.org/keywords/dynamic-inconsistency","display_name":"Dynamic inconsistency","score":0.3084999918937683}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.9950000047683716},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730999708175659},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5069000124931335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39500001072883606},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C40423286","wikidata":"https://www.wikidata.org/wiki/Q284172","display_name":"Selection bias","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3546000123023987},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35120001435279846},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.31940001249313354},{"id":"https://openalex.org/C127729010","wikidata":"https://www.wikidata.org/wiki/Q60165","display_name":"Dynamic inconsistency","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.29809999465942383},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28139999508857727},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C2983427547","wikidata":"https://www.wikidata.org/wiki/Q93200","display_name":"Gender bias","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2601.20791","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2601.20791","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.20791","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2601.20791","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.5902220010757446,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-to-video":[0],"(T2V)":[1],"diffusion":[2],"models":[3,41],"have":[4],"achieved":[5],"rapid":[6],"progress,":[7],"yet":[8],"their":[9],"demographic":[10,37,82,139],"biases,":[11],"particularly":[12],"gender":[13,55],"bias,":[14],"remain":[15],"largely":[16],"unexplored.":[17],"We":[18,34,61,113],"present":[19],"FairT2V,":[20],"a":[21,66,109,116],"training-free":[22],"debiasing":[23,102],"framework":[24],"for":[25,58],"text-to-video":[26],"generation":[27],"that":[28,44,69,135],"mitigates":[29,81],"encoder-induced":[30],"bias":[31,38,72,83,140],"without":[32],"finetuning.":[33],"first":[35],"analyze":[36],"in":[39,73],"T2V":[40,131],"and":[42],"show":[43,134],"it":[45],"primarily":[46],"originates":[47],"from":[48],"pretrained":[49],"text":[50],"encoders,":[51],"which":[52],"encode":[53],"implicit":[54],"associations":[56],"even":[57],"neutral":[59],"prompts.":[60],"quantify":[62],"this":[63,78],"effect":[64],"with":[65,71,124,143],"gender-leaning":[67],"score":[68],"correlates":[70],"generated":[74],"videos.":[75],"Based":[76],"on":[77,128,146],"insight,":[79],"FairT2V":[80,136],"by":[84],"neutralizing":[85],"prompt":[86],"embeddings":[87],"via":[88],"anchor-based":[89],"spherical":[90],"geodesic":[91],"transformations":[92],"while":[93],"preserving":[94],"semantics.":[95],"To":[96],"maintain":[97],"temporal":[98],"coherence,":[99],"we":[100],"apply":[101],"only":[103],"during":[104],"early":[105],"identity-forming":[106],"steps":[107],"through":[108],"dynamic":[110],"denoising":[111],"schedule.":[112],"further":[114],"propose":[115],"video-level":[117],"fairness":[118],"evaluation":[119],"protocol":[120],"combining":[121],"VideoLLM-based":[122],"reasoning":[123],"human":[125],"verification.":[126],"Experiments":[127],"the":[129],"modern":[130],"model":[132],"Open-Sora":[133],"substantially":[137],"reduces":[138],"across":[141],"occupations":[142],"minimal":[144],"impact":[145],"video":[147],"quality.":[148]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-01-30T00:00:00"}