{"id":"https://openalex.org/W7161968796","doi":"https://doi.org/10.48550/arxiv.2605.21195","title":"RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution","display_name":"RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161968796","doi":"https://doi.org/10.48550/arxiv.2605.21195"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21195","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.2605.21195","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136674356","display_name":"Siyong Jian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian, Siyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136635029","display_name":"Siyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Siyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066093415","display_name":"Luyuan Zhang","orcid":"https://orcid.org/0000-0001-9972-0742"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Luyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136659441","display_name":"Zedong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zedong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136670646","display_name":"Xin Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136648059","display_name":"Li, Ying, 1972, Mar. 31-","orcid":"https://orcid.org/0000-0003-2126-2459"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136668607","display_name":"Cheng Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136672575","display_name":"Huan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Huan","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":0.9074000120162964,"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":0.9074000120162964,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.008799999952316284,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.006099999882280827,"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/autoregressive-model","display_name":"Autoregressive model","score":0.7020999789237976},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6450999975204468},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.4625999927520752},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.43459999561309814},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.413100004196167},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.41200000047683716},{"id":"https://openalex.org/keywords/discrete-time-and-continuous-time","display_name":"Discrete time and continuous time","score":0.40689998865127563}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7020999789237976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6868000030517578},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6450999975204468},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5461999773979187},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4625999927520752},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43459999561309814},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.413100004196167},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.30219998955726624},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27149999141693115},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2653999924659729}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21195","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.2605.21195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21195","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":{"Discrete":[0],"autoregressive":[1],"(AR)":[2],"text-to-image":[3],"(T2I)":[4],"models":[5],"pair":[6],"a":[7,42,115,128,136],"VQ":[8,25],"tokenizer":[9],"with":[10],"an":[11],"AR":[12,53],"policy,":[13],"and":[14],"current":[15],"post-training":[16,103],"pipelines":[17],"optimize":[18],"only":[19],"the":[20,24,38,65,68,74,79,100,112,147],"policy":[21,66,113],"while":[22,88,132],"keeping":[23],"decoder":[26,80,183],"frozen.":[27],"Recent":[28],"diffusion":[29],"T2I":[30,107],"work,":[31],"exemplified":[32],"by":[33,135],"REPA-E,":[34],"has":[35],"shown":[36],"that":[37,57,84,150,182],"VAE":[39],"itself":[40],"constitutes":[41],"key":[43],"alignment":[44,130],"bottleneck,":[45],"yet":[46],"no":[47],"analogous":[48],"investigation":[49],"exists":[50],"for":[51,105],"discrete":[52,106],"models.":[54],"We":[55],"show":[56],"policy-only":[58],"optimization":[59,188],"induces":[60],"Latent":[61],"Covariate":[62],"Shift:":[63],"as":[64],"evolves,":[67],"resulting":[69],"token":[70],"distribution":[71,76],"diverges":[72],"from":[73],"ground-truth":[75],"on":[77,154,173,178],"which":[78],"was":[81],"trained,":[82],"such":[83],"reward":[85,187],"scores":[86],"improve":[87],"decoded":[89],"image":[90],"quality":[91,191],"degrades.":[92],"To":[93],"address":[94],"this":[95],"mismatch,":[96],"we":[97],"propose":[98],"RankE,":[99],"first":[101],"end-to-end":[102],"framework":[104],"generation.":[108],"Rather":[109],"than":[110],"optimizing":[111],"against":[114],"fixed":[116],"decoder,":[117],"RankE":[118,165],"co-evolves":[119],"both":[120,167],"components":[121],"through":[122],"alternating":[123],"optimization:":[124],"each":[125],"module":[126],"maximizes":[127],"ranking-based":[129],"objective":[131],"being":[133],"regularized":[134],"stability-preserving":[137],"anchor":[138],"suited":[139],"to":[140],"its":[141],"parameter":[142],"space.":[143],"This":[144],"co-evolution":[145,184],"breaks":[146],"fidelity--alignment":[148],"trade-off":[149],"plagues":[151],"frozen-decoder":[152],"approaches:":[153],"LlamaGen-XL":[155],"(775M),":[156],"standard":[157],"RL":[158],"improves":[159,166],"CLIP":[160,171],"but":[161],"degrades":[162],"FID,":[163],"whereas":[164],"simultaneously":[168],"(FID":[169],"15.21,":[170],"33.76":[172],"MS-COCO":[174],"30K).":[175],"Consistent":[176],"gains":[177],"Janus-Pro":[179],"(1B)":[180],"confirm":[181],"reliably":[185],"converts":[186],"into":[189],"pixel-space":[190],"improvements.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}