{"id":"https://openalex.org/W7162030698","doi":"https://doi.org/10.48550/arxiv.2605.20640","title":"Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics","display_name":"Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7162030698","doi":"https://doi.org/10.48550/arxiv.2605.20640"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20640","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20640","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20640","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136723276","display_name":"Yunlong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yunlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136676890","display_name":"Jinjin Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Jinjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040940904","display_name":"Wenbin Gao","orcid":"https://orcid.org/0000-0002-4037-6235"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Wenbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136706846","display_name":"Xuran Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xuran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136691592","display_name":"Runyu Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Runyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136667330","display_name":"Ying Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Ying","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9569000005722046,"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":0.9569000005722046,"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":0.016499999910593033,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.0052999998442828655,"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/overfitting","display_name":"Overfitting","score":0.7946000099182129},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5914999842643738},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5153999924659729},{"id":"https://openalex.org/keywords/portrait","display_name":"Portrait","score":0.48179998993873596},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4616999924182892},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4251999855041504},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.36880001425743103}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7946000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5928999781608582},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5914999842643738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5789999961853027},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5153999924659729},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48410001397132874},{"id":"https://openalex.org/C162462552","wikidata":"https://www.wikidata.org/wiki/Q134307","display_name":"Portrait","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4616999924182892},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.364300012588501},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.33070001006126404},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C2779271205","wikidata":"https://www.wikidata.org/wiki/Q1053973","display_name":"Temptation","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2685000002384186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20640","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20640","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20640","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20640","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":"Preprint"},"sustainable_development_goals":[{"score":0.713958203792572,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"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-image":[0],"diffusion":[1],"models":[2,137],"often":[3,38],"face":[4],"a":[5,61,73],"severe":[6],"trilemma":[7],"in":[8],"human":[9],"portrait":[10],"generation:":[11],"text-image":[12,159],"alignment,":[13,160],"photorealism,":[14,161],"and":[15,50,88,154,162],"human-perceived":[16,140,163],"aesthetics":[17],"inherently":[18],"inhibit":[19],"one":[20],"another.":[21],"Supervised":[22],"Fine-Tuning":[23],"(SFT)":[24],"is":[25],"an":[26],"effective":[27],"method":[28,107,126,149],"for":[29,65],"enhancing":[30],"the":[31,43,92,98,114,151],"photorealism":[32],"of":[33,95],"image":[34,48,93],"generation.":[35],"However,":[36],"it":[37],"leads":[39],"to":[40,42,91,138],"overfitting":[41],"training":[44,99],"dataset,":[45],"corrupts":[46],"pre-trained":[47,134],"priors,":[49],"degrades":[51],"alignment":[52,76],"or":[53],"aesthetics.":[54,141,164],"To":[55],"break":[56],"this":[57],"bottleneck,":[58],"we":[59,71],"propose":[60],"feature":[62],"supervision":[63,90],"paradigm":[64],"Multimodal":[66],"Diffusion":[67],"Transformers":[68],"(MM-DiT).":[69],"Specifically,":[70],"introduce":[72],"lightweight":[74],"cross-modal":[75],"mechanism":[77],"that":[78,147],"implicitly":[79],"extracts":[80],"multi-granularity":[81,130],"vision-aligned":[82,109],"text":[83,110],"representations":[84],"from":[85,133],"SigLIP":[86],"2":[87],"applies":[89],"branch":[94],"MM-DiT":[96],"during":[97],"stage,":[100],"with":[101],"zero":[102],"extra":[103],"inference":[104],"overhead.":[105],"Our":[106],"injects":[108],"guidance":[111],"while":[112],"preserving":[113],"base":[115],"model's":[116],"original":[117],"generalization,":[118],"avoiding":[119],"degradation":[120],"caused":[121],"by":[122],"SFT.":[123],"Furthermore,":[124],"our":[125,148],"directly":[127],"mines":[128],"implicit":[129],"aesthetic":[131],"signals":[132],"vision":[135],"foundation":[136],"optimize":[139],"Extensive":[142],"experiments":[143],"on":[144],"MM-DiTs":[145],"show":[146],"pushes":[150],"Pareto":[152],"frontier":[153],"achieves":[155],"synergistic":[156],"improvements":[157],"across":[158]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}
