{"id":"https://openalex.org/W7160990639","doi":"https://doi.org/10.48550/arxiv.2605.11061","title":"HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer","display_name":"HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160990639","doi":"https://doi.org/10.48550/arxiv.2605.11061"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.11061","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11061","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.2605.11061","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136074609","display_name":"Qi Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136070147","display_name":"Jingwen Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jingwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136010495","display_name":"Chengmin Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Chengmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120131715","display_name":"Zijian Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Zijian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136085440","display_name":"Yehao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yehao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136034992","display_name":"Yingwei Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Yingwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136042751","display_name":"Yi Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024833177","display_name":"Zhaofan Qiu","orcid":"https://orcid.org/0000-0002-7485-9198"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Zhaofan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136033596","display_name":"Kai Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136022161","display_name":"Yiheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yiheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136067384","display_name":"Hao Ai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ai, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021017043","display_name":"Siying Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Siying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136078622","display_name":"Yang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136045354","display_name":"Zhihui Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhihui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136023025","display_name":"Fengbin Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Fengbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136003471","display_name":"Ying Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Ying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136079261","display_name":"Dong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008435","display_name":"Zhen Shen","orcid":"https://orcid.org/0000-0002-3402-0910"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Zhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136009030","display_name":"Leilei Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Leilei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136046661","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0003-4934-5934"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136022936","display_name":"Siyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Siyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136082158","display_name":"Yimeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yimeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136004018","display_name":"Rui Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136082154","display_name":"Ting Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136031289","display_name":"Tao Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei, Tao","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":0.4641000032424927,"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":0.4641000032424927,"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":0.18209999799728394,"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/T12377","display_name":"Digital Humanities and Scholarship","score":0.044199999421834946,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6629999876022339},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.642300009727478},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6017000079154968},{"id":"https://openalex.org/keywords/unified-model","display_name":"Unified Model","score":0.5630000233650208},{"id":"https://openalex.org/keywords/unification","display_name":"Unification","score":0.5328999757766724},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5070000290870667},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.4530999958515167},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4284000098705292}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7692000269889832},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6629999876022339},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.642300009727478},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6017000079154968},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.5630000233650208},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5070000290870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4724999964237213},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.4530999958515167},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4284000098705292},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3871000111103058},{"id":"https://openalex.org/C44210515","wikidata":"https://www.wikidata.org/wiki/Q16968978","display_name":"Bespoke","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.2524999976158142},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.11061","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11061","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.2605.11061","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.11061","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"evolution":[1],"of":[2,73,161,200],"visual":[3,49],"generative":[4,30,185],"models":[5,147],"has":[6],"long":[7],"been":[8],"constrained":[9],"by":[10],"fragmented":[11],"architectures":[12,44,203],"relying":[13],"on":[14],"disjoint":[15,93],"text":[16,57,95],"encoders":[17],"and":[18,59,104,128,187,204],"external":[19],"VAEs.":[20],"In":[21],"this":[22,162,178],"report,":[23],"we":[24,164],"present":[25],"HiDream-O1-Image,":[26],"a":[27,39,63,70,108,206],"natively":[28,201],"unified":[29,202],"foundation":[31],"model":[32,99],"via":[33],"pixel-space":[34],"Diffusion":[35],"Transformer,":[36],"that":[37,116,177],"pioneers":[38],"paradigm":[40,85],"shift":[41],"from":[42],"modular":[43],"to":[45,100,156,170],"an":[46,77],"end-to-end":[47],"in-context":[48,110],"generation":[50,103,121],"engine.":[51],"By":[52],"mapping":[53],"raw":[54],"image":[55],"pixels,":[56],"tokens,":[58],"task-specific":[60],"conditions":[61],"into":[62],"single":[64],"shared":[65],"token":[66],"space,":[67],"HiDream-O1-Image":[68,117,136,195],"achieves":[69,138],"structural":[71],"unification":[72],"multimodal":[74,212],"inputs":[75],"within":[76],"Unified":[78],"Transformer":[79],"(UiT)":[80],"architecture.":[81],"This":[82],"native":[83],"encoding":[84],"eliminates":[86],"the":[87,98,158,167,197],"need":[88],"for":[89],"separate":[90],"VAEs":[91],"or":[92,142],"pre-trained":[94],"encoders,":[96],"allowing":[97],"treat":[101],"diverse":[102],"editing":[105],"tasks":[106],"as":[107],"consistent":[109],"reasoning":[111],"process.":[112],"Extensive":[113],"experiments":[114],"show":[115],"excels":[118],"across":[119],"various":[120],"tasks,":[122],"including":[123],"text-to-image":[124],"generation,":[125],"instruction-based":[126],"editing,":[127],"subject-driven":[129],"personalization.":[130],"Notably,":[131],"with":[132,141,148],"only":[133],"8B":[134],"parameters,":[135],"(8B)":[137],"performance":[139],"parity":[140],"even":[143],"surpasses":[144],"established":[145],"state-of-the-art":[146,192],"significantly":[149],"larger":[150],"parameters":[151],"(e.g.,":[152],"27B":[153],"Qwen-Image).":[154],"Crucially,":[155],"validate":[157],"immense":[159,198],"scalability":[160],"paradigm,":[163],"successfully":[165],"scale":[166],"architecture":[168],"up":[169],"over":[171],"200B":[172],"parameters.":[173],"Experimental":[174],"results":[175],"demonstrate":[176],"massive-scale":[179],"version":[180],"HiDream-O1-Image-Pro":[181],"(200B+)":[182],"unlocks":[183],"unprecedented":[184],"capabilities":[186],"superior":[188],"performance,":[189],"establishing":[190],"new":[191],"benchmarks.":[193],"Ultimately,":[194],"highlights":[196],"potential":[199],"charts":[205],"highly":[207],"scalable":[208],"path":[209],"toward":[210],"next-generation":[211],"AI.":[213]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-14T00:00:00"}