{"id":"https://openalex.org/W7166016083","doi":"https://doi.org/10.48550/arxiv.2606.27377","title":"DanceOPD: On-Policy Generative Field Distillation","display_name":"DanceOPD: On-Policy Generative Field Distillation","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166016083","doi":"https://doi.org/10.48550/arxiv.2606.27377"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.27377","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139416347","display_name":"Wei Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139393847","display_name":"Xiongwei Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Xiongwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073136550","display_name":"Zhewei Xu","orcid":"https://orcid.org/0000-0003-4718-6175"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zelin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139430261","display_name":"Bo Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062128902","display_name":"Lixue Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Lixue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107311577","display_name":"Y Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yongyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139429072","display_name":"Meng Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Meng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139425660","display_name":"Leigang Qu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qu, Leigang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139445075","display_name":"Lingdong Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Lingdong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139400952","display_name":"Wei Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139412914","display_name":"Tat-Seng Chua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chua, Tat-Seng","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":0.9351999759674072,"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":0.9351999759674072,"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":0.021199999377131462,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/generative-grammar","display_name":"Generative grammar","score":0.7821000218391418},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6464999914169312},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4652000069618225},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.460999995470047},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4456000030040741},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.4429999887943268},{"id":"https://openalex.org/keywords/generative-design","display_name":"Generative Design","score":0.4348999857902527},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4154999852180481}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7821000218391418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6904000043869019},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6464999914169312},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.460999995470047},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.4429999887943268},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44279998540878296},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.4348999857902527},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C91188154","wikidata":"https://www.wikidata.org/wiki/Q186247","display_name":"Vector field","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32409998774528503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30979999899864197},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2847999930381775},{"id":"https://openalex.org/C2992829110","wikidata":"https://www.wikidata.org/wiki/Q3921615","display_name":"First generation","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C2985179714","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Work flow","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.27377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":{"Modern":[0],"image":[1,57],"generation":[2,58,160],"demands":[3],"a":[4,53,92,103,167],"single":[5],"model":[6,59],"that":[7,76,148],"unifies":[8],"diverse":[9],"capabilities,":[10],"including":[11],"text-to-image":[12],"(T2I),":[13],"local":[14,40],"editing,":[15,141],"and":[16,26,39,89,144],"global":[17,38],"editing.":[18],"However,":[19],"these":[20,49],"capabilities":[21,50,156],"are":[22],"rarely":[23],"naturally":[24],"aligned":[25],"often":[27],"conflict.":[28],"For":[29],"instance,":[30],"editing":[31,41],"tends":[32],"to":[33,80,123],"degrade":[34],"T2I":[35],"performance,":[36],"while":[37,157],"interfere":[42],"with":[43,91],"each":[44,78,98],"other.":[45],"Consequently,":[46],"effectively":[47],"composing":[48],"has":[51],"become":[52],"central":[54],"challenge":[55],"for":[56,73,170],"training.":[60],"To":[61],"tackle":[62],"this,":[63],"we":[64],"introduce":[65],"DanceOPD,":[66],"an":[67],"on-policy":[68],"generative":[69,171],"field":[70,105,172],"distillation":[71,173],"framework":[72],"flow-matching":[74,175],"models":[75],"routes":[77],"sample":[79],"one":[81,85],"capability":[82,99],"field,":[83],"queries":[84],"low-noise":[86],"student-induced":[87],"state,":[88],"trains":[90],"simple":[93],"velocity":[94,104],"MSE":[95],"objective.":[96],"With":[97],"source":[100],"defined":[101],"as":[102,134],"over":[106],"the":[107,112],"shared":[108],"flow":[109],"state":[110],"space,":[111],"student":[113],"learns":[114],"from":[115],"fields":[116,132],"queried":[117],"on":[118,139],"its":[119],"own":[120],"rollout":[121],"states":[122],"compose":[124],"expert":[125],"capabilities.":[126],"This":[127],"formulation":[128],"also":[129],"absorbs":[130],"operator-defined":[131],"such":[133],"classifier-free":[135],"guidance.":[136],"Comprehensive":[137],"experiments":[138],"T2I,":[140],"realism-field":[142],"absorption,":[143],"CFG":[145],"absorption":[146],"show":[147],"our":[149],"approach":[150],"improves":[151],"multi-capability":[152],"composition,":[153],"strengthening":[154],"target":[155],"preserving":[158],"anchor":[159],"quality.":[161],"We":[162],"believe":[163],"this":[164],"work":[165],"establishes":[166],"practical":[168],"route":[169],"in":[174],"models.":[176]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-27T00:00:00"}
