{"id":"https://openalex.org/W7147748804","doi":"https://doi.org/10.48550/arxiv.2603.27115","title":"SJD-VP: Speculative Jacobi Decoding with Verification Prediction for Autoregressive Image Generation","display_name":"SJD-VP: Speculative Jacobi Decoding with Verification Prediction for Autoregressive Image Generation","publication_year":2026,"publication_date":"2026-03-28","ids":{"openalex":"https://openalex.org/W7147748804","doi":"https://doi.org/10.48550/arxiv.2603.27115"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27115","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27115","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.2603.27115","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128662335","display_name":"Bingqi Shan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shan, Bingqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128681233","display_name":"Baoquan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Baoquan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004199412","display_name":"Xiaochen Qi","orcid":"https://orcid.org/0009-0006-4081-895X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Xiaochen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132625244","display_name":"Xutao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xutao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132657477","display_name":"Yunming Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Yunming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132615407","display_name":"Liqiang Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Liqiang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5128662335"],"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":0.9552000164985657,"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":0.9552000164985657,"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/T11019","display_name":"Image Enhancement Techniques","score":0.006599999964237213,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.0031999999191612005,"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/security-token","display_name":"Security token","score":0.8246999979019165},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7728999853134155},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7477999925613403},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6521999835968018},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.578499972820282},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5109000205993652},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.38850000500679016}],"concepts":[{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.8246999979019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7760999798774719},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7728999853134155},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7477999925613403},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.578499972820282},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4772999882698059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4011000096797943},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C2983703474","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Probability estimation","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32510000467300415},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27115","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27115","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.2603.27115","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27115","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Speculative":[0,96],"Jacobi":[1,97],"Decoding":[2,98],"(SJD)":[3],"has":[4],"emerged":[5],"as":[6],"a":[7,71,94],"promising":[8],"method":[9,163],"for":[10],"accelerating":[11],"autoregressive":[12,166],"image":[13,170],"generation.":[14],"Despite":[15],"its":[16],"potential,":[17],"existing":[18,151],"SJD":[19,152],"approaches":[20],"often":[21],"suffer":[22],"from":[23,45],"the":[24,46,56,84,109,136],"low":[25],"acceptance":[26,137],"rate":[27],"issue":[28,43],"of":[29,59],"speculative":[30],"tokens":[31,75,120,128],"due":[32],"to":[33,40,53,82,107,116,131],"token":[34,48,112],"selection":[35],"ambiguity.":[36],"Recent":[37],"works":[38],"attempt":[39],"mitigate":[41],"this":[42,62],"primarily":[44],"relaxed":[47],"verification":[49],"perspective":[50],"but":[51],"fail":[52],"fully":[54],"exploit":[55],"iterative":[57],"dynamics":[58],"decoding.":[60],"In":[61,139],"paper,":[63],"we":[64,92],"conduct":[65],"an":[66],"in-depth":[67],"analysis":[68],"and":[69,86,145],"make":[70],"novel":[72,95],"observation":[73],"that":[74,160],"whose":[76,121],"probabilities":[77,113,122],"increase":[78],"are":[79,129],"more":[80],"likely":[81,130],"match":[83],"verification-accepted":[85],"correct":[87],"token.":[88],"Based":[89],"on":[90,156],"this,":[91],"propose":[93],"with":[99],"Verification":[100],"Prediction":[101],"(SJD-VP).":[102],"The":[103],"key":[104],"idea":[105],"is":[106,143],"leverage":[108],"change":[110],"in":[111],"across":[114],"iterations":[115],"guide":[117],"sampling,":[118],"favoring":[119],"increase.":[123],"This":[124],"effectively":[125],"predicts":[126],"which":[127],"pass":[132],"subsequent":[133],"verification,":[134],"boosting":[135],"rate.":[138],"particular,":[140],"our":[141,161],"SJD-VP":[142,162],"plug-and-play":[144],"can":[146],"be":[147],"seamlessly":[148],"integrated":[149],"into":[150],"methods.":[153],"Extensive":[154],"experiments":[155],"standard":[157],"benchmarks":[158],"demonstrate":[159],"consistently":[164],"accelerates":[165],"decoding":[167],"while":[168],"improving":[169],"generation":[171],"quality.":[172]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}