{"id":"https://openalex.org/W4404573412","doi":"https://doi.org/10.48550/arxiv.2411.11925","title":"Continuous Speculative Decoding for Autoregressive Image Generation","display_name":"Continuous Speculative Decoding for Autoregressive Image Generation","publication_year":2024,"publication_date":"2024-11-18","ids":{"openalex":"https://openalex.org/W4404573412","doi":"https://doi.org/10.48550/arxiv.2411.11925"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2411.11925","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.11925","pdf_url":"https://arxiv.org/pdf/2411.11925","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2411.11925","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100693880","display_name":"Zili Wang","orcid":"https://orcid.org/0000-0002-5003-3092"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zili","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089588084","display_name":"Robert Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101713583","display_name":"Kun Ding","orcid":"https://orcid.org/0000-0003-0657-1608"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115602230","display_name":"Qi Yang","orcid":"https://orcid.org/0000-0002-4930-9661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325749","display_name":"Fei Li","orcid":"https://orcid.org/0000-0001-5934-4869"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5040673285","display_name":"Shiming Xiang","orcid":"https://orcid.org/0000-0002-2089-9733"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang, Shiming","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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9812999963760376,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9812999963760376,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9452999830245972,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.935699999332428,"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/autoregressive-model","display_name":"Autoregressive model","score":0.8890373706817627},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6772034764289856},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6450085639953613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48635226488113403},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3733963966369629},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.291725754737854},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2387019395828247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22620055079460144}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.8890373706817627},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6772034764289856},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6450085639953613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48635226488113403},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3733963966369629},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.291725754737854},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2387019395828247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22620055079460144}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2411.11925","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.11925","pdf_url":"https://arxiv.org/pdf/2411.11925","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:arXiv.org:2411.11925","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2411.11925","pdf_url":"https://arxiv.org/pdf/2411.11925","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2411.11925","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2411.11925","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2411.11925","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.11925","pdf_url":"https://arxiv.org/pdf/2411.11925","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2171218219","https://openalex.org/W1972271943","https://openalex.org/W2150410159","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2156628102"],"abstract_inverted_index":{"Continuous":[0],"visual":[1,37],"autoregressive":[2],"(AR)":[3],"models":[4,31,164],"have":[5],"demonstrated":[6],"promising":[7],"performance":[8],"in":[9,18,53,151],"image":[10,182],"generation,":[11],"but":[12],"their":[13],"inherently":[14],"sequential":[15],"nature":[16],"results":[17],"slow":[19],"inference":[20],"speed.":[21],"Speculative":[22],"decoding,":[23,67],"a":[24,96,111],"successful":[25],"acceleration":[26],"technique":[27],"for":[28,47],"large":[29],"language":[30],"(LLMs),":[32],"has":[33],"effectively":[34,154],"accelerated":[35],"discrete":[36],"AR":[38,56],"models.":[39,57],"However,":[40],"the":[41,141,181],"absence":[42],"of":[43],"an":[44,108,133],"analogous":[45],"theory":[46],"continuous":[48,55,65],"distributions":[49],"precludes":[50],"its":[51],"use":[52],"accelerating":[54],"To":[58],"fill":[59],"this":[60,62],"gap,":[61],"work":[63],"presents":[64],"speculative":[66],"and":[68,84,87,121,167],"addresses":[69],"challenges":[70],"from:":[71],"1)":[72],"low":[73,104],"acceptance":[74,105],"rate,":[75],"caused":[76,94],"by":[77,82,95],"inconsistent":[78],"output":[79],"distribution":[80,90],"modeled":[81],"target":[83],"draft":[85],"models,":[86],"2)":[88],"modified":[89],"without":[91],"analytic":[92],"expression,":[93],"complex":[97],"integral.":[98,142],"For":[99,124],"challenge":[100,125],"1),":[101],"we":[102,127],"address":[103],"rates":[106],"through":[107],"approximated":[109],"criterion,":[110],"novel":[112],"denoising":[113,145],"trajectory":[114,146],"alignment":[115,147],"strategy":[116],"based":[117],"on":[118,162],"reparameterization":[119],"proximity,":[120],"token":[122],"pre-filling.":[123],"2),":[126],"introduce":[128],"acceptance-rejection":[129,152],"sampling":[130],"algorithm":[131],"with":[132],"appropriate":[134],"upper":[135],"bound,":[136],"thereby":[137],"avoiding":[138,155],"explicitly":[139],"calculating":[140],"Furthermore,":[143],"our":[144,172],"is":[148,186],"also":[149],"reused":[150],"sampling,":[153],"repetitive":[156],"diffusion":[157],"model":[158],"inference.":[159],"Extensive":[160],"experiments":[161],"various":[163],"at":[165],"256x256":[166],"512x512":[168],"resolutions":[169],"demonstrate":[170],"that":[171],"approach":[173],"achieves":[174],"over":[175],"2x":[176],"wall-time":[177],"speedup":[178],"while":[179],"preserving":[180],"generation":[183],"quality.":[184],"Codes":[185],"available":[187],"at:":[188],"https://github.com/MarkXCloud/CSpD":[189]},"counts_by_year":[],"updated_date":"2026-07-03T06:15:21.484131","created_date":"2025-10-10T00:00:00"}