{"id":"https://openalex.org/W4399758697","doi":"https://doi.org/10.48550/arxiv.2406.09570","title":"Improving Consistency Models with Generator-Augmented Flows","display_name":"Improving Consistency Models with Generator-Augmented Flows","publication_year":2024,"publication_date":"2024-06-13","ids":{"openalex":"https://openalex.org/W4399758697","doi":"https://doi.org/10.48550/arxiv.2406.09570"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2406.09570","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.09570","pdf_url":"https://arxiv.org/pdf/2406.09570","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2406.09570","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008216150","display_name":"Thibaut Issenhuth","orcid":"https://orcid.org/0000-0002-0993-4366","observed_orcids":["https://orcid.org/0000-0002-0993-4366"]},"institutions":[{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Issenhuth, Thibaut","raw_affiliation_strings":["Criteo AI Lab (Paris - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab (Paris - France)","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lee, Sangchul","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lee, Sangchul","raw_affiliation_strings":["Criteo AI Lab (Paris - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab (Paris - France)","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011094173","display_name":"Ludovic Dos Santos","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Santos, Ludovic Dos","raw_affiliation_strings":["Criteo AI Lab (Paris - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab (Paris - France)","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023242895","display_name":"Jean-Yves Franceschi","orcid":"https://orcid.org/0000-0003-3631-5349","observed_orcids":["https://orcid.org/0000-0003-3631-5349"]},"institutions":[{"id":"https://openalex.org/I4210161401","display_name":"Criteo (France)","ror":"https://ror.org/04vyg0r47","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210161401"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Franceschi, Jean-Yves","raw_affiliation_strings":["Criteo AI Lab (Paris - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Criteo AI Lab (Paris - France)","institution_ids":["https://openalex.org/I4210161401"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kim, Chansoo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Chansoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031137438","display_name":"Alain Rakotomamonjy","orcid":"https://orcid.org/0000-0002-4210-7792","observed_orcids":["https://orcid.org/0000-0002-4210-7792"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rakotomamonjy, Alain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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":0.9785000085830688,"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":0.9785000085830688,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.00419999985024333,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.0034000000450760126,"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/consistency-models","display_name":"consistency models","score":0.9890000224113464},{"id":"https://openalex.org/keywords/consistency-distillation","display_name":"consistency distillation","score":0.7929999828338623},{"id":"https://openalex.org/keywords/consistency-regularization","display_name":"consistency regularization","score":0.972000002861023},{"id":"https://openalex.org/keywords/score-based-diffusion","display_name":"score-based diffusion","score":0.8199999928474426},{"id":"https://openalex.org/keywords/velocity-field-estimation","display_name":"velocity field estimation","score":0.6330000162124634},{"id":"https://openalex.org/keywords/continuous-time-limit","display_name":"continuous-time limit","score":0.6309999823570251},{"id":"https://openalex.org/keywords/convergence-acceleration","display_name":"convergence acceleration","score":0.38499999046325684}],"concepts":[{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.7219499945640564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170196175575256},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7067872285842896},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.6182680726051331},{"id":"https://openalex.org/C37279795","wikidata":"https://www.wikidata.org/wiki/Q2492305","display_name":"Consistency model","level":3,"score":0.48381274938583374},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4820431172847748},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.41738489270210266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4172884225845337},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3905060291290283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3737184703350067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35045135021209717},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17650160193443298},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.17333751916885376},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14892685413360596},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12409427762031555},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2406.09570","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.09570","pdf_url":"https://arxiv.org/pdf/2406.09570","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-04611719v1","doi":null,"is_oa":true,"landing_page_url":"https://hal.science/hal-04611719","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://hal.science/hal-04611719","raw_type":"info:eu-repo/semantics/preprint"},{"id":"doi:10.48550/arxiv.2406.09570","doi":"https://doi.org/10.48550/arxiv.2406.09570","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2406.09570","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,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2406.09570","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.09570","pdf_url":"https://arxiv.org/pdf/2406.09570","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4876063428","display_name":null,"funder_award_id":"2023-00262155","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399758697.pdf","grobid_xml":"https://content.openalex.org/works/W4399758697.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W3120478063","https://openalex.org/W4399912930","https://openalex.org/W4403573316","https://openalex.org/W4403757510"],"related_works":["https://openalex.org/W4403407107","https://openalex.org/W4387928896","https://openalex.org/W4414581693","https://openalex.org/W4414129127","https://openalex.org/W7128705537","https://openalex.org/W4404307599","https://openalex.org/W4391801159","https://openalex.org/W4404088177","https://openalex.org/W7127102689","https://openalex.org/W4323076585"],"abstract_inverted_index":{"Consistency":[0],"models":[1],"imitate":[2],"the":[3,34,39,51,81,112,117],"multi-step":[4],"sampling":[5],"of":[6,14,38,59],"score-based":[7],"diffusion":[8],"in":[9,22,80],"a":[10,15,45,54,68,90,103],"single":[11],"forward":[12],"pass":[13],"neural":[16,47],"network.":[17,48],"They":[18],"can":[19],"be":[20],"learned":[21],"two":[23],"ways:":[24],"consistency":[25,28,71,104,127],"distillation":[26,72],"and":[27,73,116],"training.":[29],"The":[30,63,136],"former":[31],"relies":[32],"on":[33],"true":[35],"velocity":[36,61],"field":[37],"corresponding":[40,99],"differential":[41],"equation,":[42],"approximated":[43],"by":[44],"pre-trained":[46],"In":[49],"contrast,":[50],"latter":[52],"uses":[53],"single-sample":[55],"Monte":[56],"Carlo":[57],"estimate":[58],"this":[60,86,109],"field.":[62],"related":[64],"estimation":[65],"error":[66],"induces":[67],"discrepancy":[69,115],"between":[70],"training":[74,128],"that,":[75],"we":[76,88],"show,":[77],"still":[78],"holds":[79],"continuous-time":[82],"limit.":[83],"To":[84],"alleviate":[85],"issue,":[87],"propose":[89],"novel":[91],"flow":[92,110],"that":[93,108],"transports":[94],"noisy":[95],"data":[96],"towards":[97],"their":[98],"outputs":[100],"derived":[101],"from":[102],"model.":[105],"We":[106],"prove":[107],"reduces":[111],"previously":[113],"identified":[114],"noise-data":[118],"transport":[119],"cost.":[120],"Consequently,":[121],"our":[122],"method":[123],"not":[124],"only":[125],"accelerates":[126],"convergence":[129],"but":[130],"also":[131],"enhances":[132],"its":[133],"overall":[134],"performance.":[135],"code":[137],"is":[138],"available":[139],"at:":[140],"https://github.com/thibautissenhuth/consistency_GC.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-06-18T00:00:00"}
