{"id":"https://openalex.org/W7162764283","doi":"https://doi.org/10.48550/arxiv.2605.30116","title":"SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation","display_name":"SGMD: Score Gradient Matching Distillation for Few-Step Video Diffusion Distillation","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162764283","doi":"https://doi.org/10.48550/arxiv.2605.30116"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30116","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.30116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024102135","display_name":"Zhuguanyu Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zhuguanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137398059","display_name":"Ruihao Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Ruihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101709269","display_name":"Yang Yong","orcid":"https://orcid.org/0000-0002-3309-4643"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137332711","display_name":"Yushi Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yushi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137392414","display_name":"Xiangyu Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137356317","display_name":"Lei Yang","orcid":"https://orcid.org/0000-0002-7994-544X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137366170","display_name":"Dahua Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Dahua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137310536","display_name":"Xianglong Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xianglong","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":0.30320000648498535,"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":0.30320000648498535,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.13500000536441803,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.07649999856948853,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6883000135421753},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6578999757766724},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5722000002861023},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4154999852180481},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.3864000141620636},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3488999903202057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694100022315979},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6883000135421753},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6578999757766724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.572700023651123},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4465999901294708},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4011000096797943},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2791999876499176},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30116","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2605.30116","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30116","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.6414219737052917,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Distribution":[0],"Matching":[1,63],"Distillation":[2,64],"(DMD)":[3],"is":[4,155,172],"a":[5,30,68,86,92,108],"widely":[6],"used":[7],"paradigm":[8],"for":[9,50,115,121,141],"accelerating":[10],"inference":[11],"in":[12,157],"few-step":[13],"video":[14,19],"diffusion":[15],"models.":[16],"However,":[17],"DMD-style":[18],"distillation":[20],"faces":[21],"two":[22],"coupled":[23],"challenges:":[24],"the":[25,74,78],"fake":[26,75],"score":[27,76],"must":[28],"track":[29],"continuously":[31],"evolving":[32],"generator,":[33],"making":[34],"training":[35,134],"costly":[36],"when":[37],"frequent":[38],"updates":[39],"are":[40],"required,":[41],"while":[42,80,145,163],"reverse-KL-style":[43],"matching":[44],"can":[45],"be":[46],"mode-seeking":[47],"and":[48,118,136,160,166],"conservative":[49],"preserving":[51,146],"strong":[52],"motion":[53,139,158],"dynamics.":[54],"To":[55],"address":[56],"these":[57],"issues,":[58],"we":[59],"propose":[60],"\\textbf{Score":[61],"Gradient":[62],"(SGMD)}.":[65],"SGMD":[66,106,128,154],"adopts":[67],"fake-score":[69],"perspective":[70],"by":[71],"directly":[72],"optimizing":[73],"toward":[77],"teacher,":[79],"using":[81],"teacher":[82],"stop-gradient":[83],"Fisher":[84],"as":[85],"stable":[87],"distribution-matching":[88],"objective.":[89],"We":[90],"provide":[91],"gradient":[93],"analysis":[94],"that":[95,153],"motivates":[96],"this":[97],"objective":[98],"choice":[99],"under":[100],"ideal":[101],"tracking.":[102,123],"Building":[103],"on":[104],"this,":[105],"introduces":[107],"pair":[109],"of":[110],"dual":[111],"potentials:":[112],"negative-residual":[113],"(NR)":[114],"outer-loop":[116],"correction":[117],"residual-contraction":[119],"(RC)":[120],"inner-loop":[122],"Empirically,":[124],"compared":[125],"to":[126],"DMD2,":[127],"achieves":[129],"an":[130],"approximately":[131],"$\\sim":[132],"3\\times$":[133],"speedup":[135],"substantially":[137],"improves":[138],"dynamics":[140],"4-step":[142],"distilled":[143],"models":[144],"temporal":[147],"consistency.":[148],"A":[149],"human":[150],"study":[151],"confirms":[152],"preferred":[156],"quality":[159,165],"overall":[161],"preference,":[162],"visual":[164],"text":[167],"alignment":[168],"remain":[169],"comparable.":[170],"Code":[171],"available":[173],"at":[174],"https://github.com/ModelTC/LightX2V.":[175]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-30T00:00:00"}
