{"id":"https://openalex.org/W7154180940","doi":"https://doi.org/10.48550/arxiv.2604.09168","title":"ELT: Elastic Looped Transformers for Visual Generation","display_name":"ELT: Elastic Looped Transformers for Visual Generation","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154180940","doi":"https://doi.org/10.48550/arxiv.2604.09168"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09168","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09168","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09168","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091199866","display_name":"Sahil Goyal","orcid":"https://orcid.org/0000-0002-8209-5167"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Goyal, Sahil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133486443","display_name":"Swayam Agrawal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agrawal, Swayam","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116339239","display_name":"Gautham Govind Anil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anil, Gautham Govind","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034432097","display_name":"Prateek Jain","orcid":"https://orcid.org/0000-0002-8191-9785"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Prateek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683993","display_name":"Sujoy Paul","orcid":"https://orcid.org/0000-0001-6798-302X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paul, Sujoy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058266558","display_name":"Aditya Kusupati","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kusupati, Aditya","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5091199866"],"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":0.8894000053405762,"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":0.8894000053405762,"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/T11448","display_name":"Face recognition and analysis","score":0.021800000220537186,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.016499999910593033,"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":0.8112999796867371},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5302000045776367},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5231999754905701},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4309999942779541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33640000224113464},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.2930000126361847}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.8112999796867371},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5231999754905701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5095000267028809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4876999855041504},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4309999942779541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3179999887943268},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3174000084400177},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3066999912261963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2953000068664551},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C131357438","wikidata":"https://www.wikidata.org/wiki/Q208598","display_name":"Eddy current","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2678999900817871}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09168","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09168","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09168","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09168","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"introduce":[1],"Elastic":[2],"Looped":[3],"Transformers":[4],"(ELT),":[5],"a":[6,16,90,97,103,145],"highly":[7],"parameter-efficient":[8],"class":[9],"of":[10,28,63,99,148,158],"visual":[11,132],"generative":[12,22],"models":[13,23,53,101],"based":[14],"on":[15,25,150,160],"recurrent":[17],"transformer":[18,30,37],"architecture.":[19],"While":[20],"conventional":[21],"rely":[24],"deep":[26],"stacks":[27],"unique":[29],"layers,":[31],"our":[32],"approach":[33],"employs":[34],"iterative,":[35],"weight-shared":[36],"blocks":[38],"to":[39,82],"drastically":[40],"reduce":[41],"parameter":[42,123,138],"counts":[43],"while":[44],"maintaining":[45],"high":[46],"synthesis":[47],"quality.":[48],"To":[49],"effectively":[50],"train":[51],"these":[52],"for":[54,131],"image":[55],"and":[56,117,156],"video":[57],"generation,":[58],"we":[59],"propose":[60],"the":[61,76,86,121,128],"idea":[62],"Intra-Loop":[64],"Self":[65],"Distillation":[66],"(ILSD),":[67],"where":[68],"student":[69],"configurations":[70],"(intermediate":[71],"loops)":[72,81],"are":[73],"distilled":[74],"from":[75,102],"teacher":[77],"configuration":[78],"(maximum":[79],"training":[80,92,105],"ensure":[83],"consistency":[84],"across":[85],"model's":[87],"depth":[88],"in":[89,137],"single":[91,104],"step.":[93],"Our":[94],"framework":[95],"yields":[96],"family":[98],"elastic":[100],"run,":[106],"enabling":[107],"Any-Time":[108],"inference":[109],"capability":[110],"with":[111,120],"dynamic":[112],"trade-offs":[113],"between":[114],"computational":[115],"cost":[116],"generation":[118],"quality,":[119],"same":[122],"count.":[124],"ELT":[125,143],"significantly":[126],"shifts":[127],"efficiency":[129],"frontier":[130],"synthesis.":[133],"With":[134],"$4\\times$":[135],"reduction":[136],"count":[139],"under":[140],"iso-inference-compute":[141],"settings,":[142],"achieves":[144],"competitive":[146],"FID":[147],"$2.0$":[149],"class-conditional":[151,161],"ImageNet":[152],"$256":[153],"\\times":[154],"256$":[155],"FVD":[157],"$72.8$":[159],"UCF-101.":[162]},"counts_by_year":[],"updated_date":"2026-04-14T06:08:25.285971","created_date":"2026-04-14T00:00:00"}