{"id":"https://openalex.org/W7162403473","doi":"https://doi.org/10.48550/arxiv.2605.24870","title":"Trajectory-Consistent Calibration for Cache-Accelerated Diffusion Models","display_name":"Trajectory-Consistent Calibration for Cache-Accelerated Diffusion Models","publication_year":2026,"publication_date":"2026-05-24","ids":{"openalex":"https://openalex.org/W7162403473","doi":"https://doi.org/10.48550/arxiv.2605.24870"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.24870","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24870","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.24870","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137041455","display_name":"Mingyu Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Mingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137003556","display_name":"Dingkun Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Dingkun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136995612","display_name":"Jingwei Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Jingwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.3749000132083893,"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":0.3749000132083893,"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":0.2468000054359436,"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":0.05180000141263008,"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/calibration","display_name":"Calibration","score":0.6478000283241272},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5570999979972839},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.5202000141143799},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.46309998631477356},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.45509999990463257},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.45399999618530273},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.42910000681877136}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6478000283241272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5672000050544739},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5570999979972839},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5331000089645386},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.5202000141143799},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.46309998631477356},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.45399999618530273},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4318999946117401},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C75438885","wikidata":"https://www.wikidata.org/wiki/Q3403615","display_name":"Large deviations theory","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.349700003862381},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32260000705718994},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2728999853134155},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.24870","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24870","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.24870","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24870","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":"Preprint"},"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],"Transformers":[1],"require":[2],"repeated":[3],"denoiser":[4],"evaluations":[5],"during":[6],"iterative":[7,101],"sampling,":[8],"making":[9],"inference":[10],"computationally":[11],"expensive.":[12],"Cache-based":[13],"acceleration":[14,130],"reduces":[15,149],"this":[16,35,66],"cost":[17],"by":[18,53,61,113],"reusing":[19],"intermediate":[20],"representations":[21,79],"across":[22,127],"denoising":[23],"steps,":[24],"but":[25],"can":[26],"introduce":[27],"representation":[28],"deviations":[29,40],"and":[30,41,55,119],"degrade":[31],"generation":[32],"quality.":[33],"In":[34],"paper,":[36],"we":[37,68],"analyze":[38],"these":[39],"show":[42,121],"that":[43,76,104,122],"effective":[44],"calibration":[45,89],"should":[46],"consider":[47],"both":[48],"the":[49,56,109,157],"direct":[50],"mismatch":[51],"caused":[52],"reuse":[54,136],"subsequent":[57],"trajectory":[58,110],"shift":[59,111],"induced":[60,112],"earlier":[62],"corrections.":[63],"To":[64],"address":[65],"challenge,":[67],"propose":[69],"Trajectory-Consistent":[70],"Calibration":[71],"(TCC),":[72],"a":[73,92,140],"training-free":[74],"method":[75],"calibrates":[77],"cached":[78],"toward":[80],"their":[81,134],"full-computation":[82,158],"counterparts.":[83],"Specifically,":[84],"rather":[85],"than":[86],"estimating":[87],"all":[88],"priors":[90],"from":[91,151],"single":[93],"uncorrected":[94],"cache":[95],"trajectory,":[96],"TCC":[97,123,148],"uses":[98],"an":[99],"offline":[100],"procedure":[102],"so":[103],"each":[105],"prior":[106],"accounts":[107],"for":[108],"preceding":[114],"calibrations.":[115],"Experiments":[116],"on":[117,146],"PixArt-alpha":[118,142],"DiT-XL/2":[120],"consistently":[124],"improves":[125],"FID":[126,150],"representative":[128,141],"cache-based":[129],"methods":[131],"while":[132],"preserving":[133],"underlying":[135],"policies.":[137],"Notably,":[138],"in":[139],"cache-acceleration":[143],"setting":[144],"based":[145],"FORA,":[147],"29.83":[152],"to":[153],"27.35,":[154],"slightly":[155],"surpassing":[156],"baseline.":[159]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}
