{"id":"https://openalex.org/W4416017174","doi":"https://doi.org/10.1145/3746252.3761406","title":"Flexiffusion: Training-Free Segment-Wise Neural Architecture Search for Efficient Diffusion Models","display_name":"Flexiffusion: Training-Free Segment-Wise Neural Architecture Search for Efficient Diffusion Models","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416017174","doi":"https://doi.org/10.1145/3746252.3761406"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761406","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024822157","display_name":"Hongtao Huang","orcid":"https://orcid.org/0009-0001-1239-1286"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hongtao Huang","raw_affiliation_strings":["University of New South Wales, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0009-0001-1239-1286","affiliations":[{"raw_affiliation_string":"University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034967388","display_name":"Xiaojun Chang","orcid":"https://orcid.org/0000-0002-7778-8807"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Chang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-7778-8807","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052731721","display_name":"Lina Yao","orcid":"https://orcid.org/0000-0002-4149-839X"},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lina Yao","raw_affiliation_strings":["CSIRO's Data61, Sydney, Australia and University of New South Wales, Sydeny, Australia"],"raw_orcid":"https://orcid.org/0000-0002-4149-839X","affiliations":[{"raw_affiliation_string":"CSIRO's Data61, Sydney, Australia and University of New South Wales, Sydeny, Australia","institution_ids":["https://openalex.org/I42894916"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3825,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85175264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"949","last_page":"959"},"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":0.926800012588501,"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":0.926800012588501,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.02019999921321869,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.008799999952316284,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/speedup","display_name":"Speedup","score":0.6898000240325928},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6057999730110168},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.53329998254776},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5160999894142151},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4812000095844269},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.45089998841285706},{"id":"https://openalex.org/keywords/iterative-and-incremental-development","display_name":"Iterative and incremental development","score":0.35420000553131104},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.33970001339912415},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.320499986410141}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746999979019165},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6898000240325928},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6057999730110168},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.53329998254776},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5160999894142151},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4812000095844269},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42730000615119934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39079999923706055},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3573000133037567},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C75235859","wikidata":"https://www.wikidata.org/wiki/Q582659","display_name":"Exponential growth","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28519999980926514},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C19889080","wikidata":"https://www.wikidata.org/wiki/Q2835852","display_name":"Beam search","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2781018962","wikidata":"https://www.wikidata.org/wiki/Q5164884","display_name":"Container (type theory)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761406","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761406","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W3034528892","https://openalex.org/W3139445856","https://openalex.org/W4312933868","https://openalex.org/W4313142698","https://openalex.org/W4386065704","https://openalex.org/W4390872297","https://openalex.org/W4390873650","https://openalex.org/W4402816687"],"related_works":[],"abstract_inverted_index":{"Diffusion":[0,192],"models":[1,6],"(DMs)":[2],"are":[3,13,34],"powerful":[4],"generative":[5],"capable":[7],"of":[8,88,147],"producing":[9],"high-fidelity":[10],"images":[11],"but":[12],"constrained":[14],"by":[15,36,153],"high":[16],"computational":[17],"costs":[18],"due":[19],"to":[20,80,119],"iterative":[21],"multi-step":[22],"inference.":[23],"While":[24],"Neural":[25],"Architecture":[26],"Search":[27],"(NAS)":[28],"can":[29],"optimize":[30],"DMs,":[31],"existing":[32],"methods":[33],"hindered":[35],"retraining":[37],"requirements,":[38],"exponential":[39],"search":[40,111],"complexity":[41],"from":[42,141],"step-wise":[43,120],"optimization,":[44],"and":[45,69,105,168,172,182],"slow":[46],"evaluation":[47,134,151],"relying":[48],"on":[49,170,190],"massive":[50],"image":[51],"generation.":[52],"To":[53],"address":[54],"these":[55],"challenges,":[56],"we":[57,127],"propose":[58],"Flexiffusion,":[59],"a":[60,132,142,200],"training-free":[61],"NAS":[62,121,137,181],"framework":[63],"that":[64,138],"jointly":[65],"optimizes":[66],"generation":[67,83],"schedules":[68],"model":[70],"architectures":[71],"without":[72,207],"modifying":[73],"pre-trained":[74],"parameters.":[75],"Our":[76,197],"key":[77],"insight":[78],"is":[79],"decompose":[81],"the":[82,114],"process":[84],"into":[85],"flexible":[86],"segments":[87],"equal":[89],"length,":[90],"where":[91],"each":[92],"segment":[93],"dynamically":[94],"combines":[95],"three":[96],"step":[97],"types:":[98],"full":[99],"(complete":[100],"computation),":[101,104],"partial":[102],"(cache-reused":[103],"null":[106],"(skipped":[107],"computation).":[108],"This":[109],"segment-wise":[110],"space":[112],"reduces":[113],"candidate":[115],"pool":[116],"exponentially":[117],"compared":[118],"while":[122],"preserving":[123],"architectural":[124],"diversity.":[125],"Further,":[126],"introduce":[128],"relative":[129],"FID":[130,175],"(rFID),":[131],"lightweight":[133],"metric":[135],"for":[136,203],"measures":[139],"divergence":[140],"teacher":[143],"model's":[144],"outputs":[145],"instead":[146],"ground":[148],"truth,":[149],"slashing":[150],"time":[152],"over":[154],"90%.":[155],"In":[156],"practice,":[157],"Flexiffusion":[158],"achieves":[159],"at":[160],"least":[161],"2\u00d7":[162],"acceleration":[163],"across":[164],"LDMs,":[165],"Stable":[166,191],"Diffusion,":[167],"DDPMs":[169],"ImageNet":[171],"MS-COCO,":[173],"with":[174,193],"degradation":[176],"under":[177],"5%,":[178],"outperforming":[179],"prior":[180],"caching":[183],"methods.":[184],"Notably,":[185],"it":[186],"attains":[187],"5.1\u00d7":[188],"speedup":[189],"near-identical":[194],"CLIP":[195],"scores.":[196],"work":[198],"pioneers":[199],"resource-efficient":[201],"paradigm":[202],"searching":[204],"high-speed":[205],"DMs":[206],"sacrificing":[208],"quality.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-11-08T00:00:00"}