{"id":"https://openalex.org/W7135191275","doi":"https://doi.org/10.48550/arxiv.2603.12245","title":"One Model, Many Budgets: Elastic Latent Interfaces for Diffusion Transformers","display_name":"One Model, Many Budgets: Elastic Latent Interfaces for Diffusion Transformers","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135191275","doi":"https://doi.org/10.48550/arxiv.2603.12245"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12245","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12245","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12245","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090496923","display_name":"Moayed Haji-Ali","orcid":"https://orcid.org/0009-0006-8224-5299"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haji-Ali, Moayed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052645912","display_name":"Willi Menapace","orcid":"https://orcid.org/0000-0002-0715-9300"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menapace, Willi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028188014","display_name":"Ivan Skorokhodov","orcid":"https://orcid.org/0000-0002-7611-9310"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Skorokhodov, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129093627","display_name":"Dogyun Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Dogyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129021672","display_name":"Anil Kag","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kag, Anil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031741585","display_name":"Michael Vasilkovsky","orcid":"https://orcid.org/0009-0007-4257-1636"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vasilkovsky, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129098974","display_name":"Sergey Tulyakov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tulyakov, Sergey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027328044","display_name":"Vicente Ord\u00f3\u00f1ez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ordonez, Vicente","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021757527","display_name":"Aliaksandr Siarohin","orcid":"https://orcid.org/0000-0001-9252-1775"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siarohin, Aliaksandr","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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":0.8618999719619751,"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":0.8618999719619751,"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":0.017799999564886093,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.014000000432133675,"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/transformer","display_name":"Transformer","score":0.632099986076355},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4325999915599823},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.426800012588501},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.3937999904155731},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.38519999384880066}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.632099986076355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.628600001335144},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.364300012588501},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.36390000581741333},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2840999960899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.273499995470047},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C174839445","wikidata":"https://www.wikidata.org/wiki/Q1134386","display_name":"Lock (firearm)","level":2,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12245","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12245","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12245","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12245","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4545515179634094}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion":[0],"transformers":[1],"(DiTs)":[2],"achieve":[3],"high":[4],"generative":[5],"quality":[6],"but":[7],"lock":[8],"FLOPs":[9],"to":[10,28,95,110,123],"image":[11,45],"resolution,":[12],"limiting":[13],"principled":[14],"latency-quality":[15],"trade-offs,":[16],"and":[17,69,78,80,141,148,168,172],"allocate":[18],"computation":[19],"uniformly":[20],"across":[21],"input":[22,44,83],"spatial":[23,76],"tokens,":[24],"wasting":[25],"resource":[26],"allocation":[27],"unimportant":[29],"regions.":[30,84],"We":[31],"introduce":[32],"Elastic":[33],"Latent":[34],"Interface":[35],"Transformer":[36],"(ELIT),":[37],"a":[38,52,55],"drop-in,":[39],"DiT-compatible":[40],"mechanism":[41],"that":[42],"decouples":[43],"size":[46],"from":[47],"compute.":[48],"Our":[49],"approach":[50],"inserts":[51],"latent":[53],"interface,":[54],"learnable":[56],"variable-length":[57],"token":[58],"sequence":[59],"on":[60],"which":[61],"standard":[62],"transformer":[63],"blocks":[64],"can":[65,119],"operate.":[66],"Lightweight":[67],"Read":[68],"Write":[70],"cross-attention":[71,133],"layers":[72,134],"move":[73],"information":[74,109],"between":[75],"tokens":[77],"latents":[79,101,118],"prioritize":[81],"important":[82],"By":[85],"training":[86],"with":[87,99],"random":[88],"dropping":[89],"of":[90,117,166],"tail":[91],"latents,":[92],"ELIT":[93,127,154,161],"learns":[94],"produce":[96],"importance-ordered":[97],"representations":[98],"earlier":[100],"capturing":[102],"global":[103],"structure":[104],"while":[105,135],"later":[106],"ones":[107],"contain":[108],"refine":[111],"details.":[112],"At":[113],"inference,":[114],"the":[115,137,142],"number":[116],"be":[120],"dynamically":[121],"adjusted":[122],"match":[124],"compute":[125],"constraints.":[126],"is":[128],"deliberately":[129],"minimal,":[130],"adding":[131],"two":[132],"leaving":[136],"rectified":[138],"flow":[139],"objective":[140],"DiT":[143],"stack":[144],"unchanged.":[145],"Across":[146],"datasets":[147],"architectures":[149],"(DiT,":[150],"U-ViT,":[151],"HDiT,":[152],"MM-DiT),":[153],"delivers":[155,162],"consistent":[156],"gains.":[157],"On":[158],"ImageNet-1K":[159],"512px,":[160],"an":[163],"average":[164],"gain":[165],"$35.3\\%$":[167],"$39.6\\%$":[169],"in":[170],"FID":[171],"FDD":[173],"scores.":[174],"Project":[175],"page:":[176],"https://snap-research.github.io/elit/":[177]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-14T00:00:00"}
