{"id":"https://openalex.org/W7134272024","doi":"https://doi.org/10.48550/arxiv.2603.06351","title":"DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking","display_name":"DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134272024","doi":"https://doi.org/10.48550/arxiv.2603.06351"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06351","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120789297","display_name":"Akash Haridas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haridas, Akash","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114858941","display_name":"Utkarsh Saxena","orcid":"https://orcid.org/0009-0007-0042-2413"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saxena, Utkarsh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069269180","display_name":"Parsa Ashrafi Fashi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fashi, Parsa Ashrafi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028862918","display_name":"Mehdi Rezagholizadeh","orcid":"https://orcid.org/0000-0003-4014-6007"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rezagholizadeh, Mehdi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128448226","display_name":"Vikram Appia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Appia, Vikram","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128494654","display_name":"Emad Barsoum","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barsoum, Emad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.6337000131607056,"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":0.6337000131607056,"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":0.07540000230073929,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.030300000682473183,"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":0.6489999890327454},{"id":"https://openalex.org/keywords/chunking","display_name":"Chunking (psychology)","score":0.6427000164985657},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6362000107765198},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5537999868392944},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41620001196861267},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4090999960899353},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4052000045776367},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.3409000039100647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7475000023841858},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6489999890327454},{"id":"https://openalex.org/C203357204","wikidata":"https://www.wikidata.org/wiki/Q1089605","display_name":"Chunking (psychology)","level":2,"score":0.6427000164985657},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6362000107765198},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5537999868392944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167999863624573},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4790000021457672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C68710425","wikidata":"https://www.wikidata.org/wiki/Q5275442","display_name":"Diffusion process","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27959999442100525},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.27630001306533813}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06351","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06351","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":"pmh:doi:10.48550/arxiv.2603.06351","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","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":{"Diffusion":[0,29],"Transformers":[1],"rely":[2],"on":[3],"static":[4],"patchify":[5],"tokenization,":[6],"assigning":[7],"the":[8,26,44,92],"same":[9],"token":[10,50],"budget":[11],"to":[12,65,74,147,154],"smooth":[13,116],"backgrounds,":[14],"detailed":[15,75],"object":[16],"regions,":[17],"noisy":[18,69],"early":[19],"timesteps,":[20,70],"and":[21,68,71,77,85,128,149,169,191],"late-stage":[22],"refinements.":[23],"We":[24],"introduce":[25],"Dynamic":[27],"Chunking":[28],"Transformer":[30],"(DC-DiT),":[31],"which":[32],"replaces":[33],"fixed":[34],"patchification":[35],"with":[36,58,114,132],"a":[37,48,53,104,115,160,181],"learned":[38,56],"encoder-router-decoder":[39],"scaffold":[40],"that":[41,177],"adaptively":[42],"compresses":[43],"2D":[45],"input":[46],"into":[47],"shorter":[49],"sequence":[51],"through":[52],"chunking":[54],"mechanism":[55,183],"end-to-end":[57],"diffusion":[59],"training.":[60],"DC-DiT":[61,120,141],"allocates":[62],"fewer":[63],"tokens":[64,73],"predictable":[66],"regions":[67,76],"more":[72,189,192],"later":[78],"refinement":[79],"stages,":[80],"yielding":[81,159],"meaningful":[82],"spatial":[83],"segmentations":[84],"timestep-adaptive":[86],"compression":[87],"schedules":[88],"without":[89],"supervision.":[90],"Furthermore,":[91],"router":[93],"provides":[94],"an":[95],"importance":[96],"ordering":[97],"over":[98,156],"retained":[99],"tokens,":[100],"enabling":[101],"elastic":[102],"inference:":[103],"single":[105],"checkpoint":[106],"can":[107,121],"be":[108,122],"evaluated":[109],"at":[110,194],"flexible":[111,193],"compute":[112],"budgets":[113],"quality-compute":[117],"tradeoff.":[118],"Additionally,":[119],"upcycled":[123],"from":[124],"pretrained":[125],"DiT":[126,157],"checkpoints":[127],"is":[129,180],"also":[130],"compatible":[131],"orthogonal":[133],"dynamic":[134],"computation":[135],"approaches.":[136],"On":[137],"class-conditional":[138],"ImageNet":[139],"generation,":[140],"reduces":[142],"inference":[143,195],"FLOPs":[144],"by":[145,152],"up":[146,153],"36.8%":[148],"improves":[150],"FID":[151],"37.8%":[155],"baselines,":[158],"stronger":[161],"quality--compute":[162],"Pareto":[163],"frontier":[164],"across":[165],"model":[166],"scales,":[167],"resolutions,":[168],"guidance":[170],"settings.":[171],"More":[172],"broadly,":[173],"these":[174],"results":[175],"suggest":[176],"adaptive":[178],"tokenization":[179],"general":[182],"for":[184],"making":[185],"visual":[186],"generation":[187],"both":[188],"efficient":[190],"time.":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-10T00:00:00"}