{"id":"https://openalex.org/W7138878422","doi":"https://doi.org/10.48550/arxiv.2603.16195","title":"S-VAM: Shortcut Video-Action Model by Self-Distilling Geometric and Semantic Foresight","display_name":"S-VAM: Shortcut Video-Action Model by Self-Distilling Geometric and Semantic Foresight","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138878422","doi":"https://doi.org/10.48550/arxiv.2603.16195"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16195","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.16195","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109886746","display_name":"Haodong Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yan, Haodong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102548895","display_name":"Zhide Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Zhide","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130114250","display_name":"Jiaguan Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Jiaguan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101621282","display_name":"Junjie He","orcid":"https://orcid.org/0000-0003-4746-2870"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Junjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090802334","display_name":"Weilin Yuan","orcid":"https://orcid.org/0000-0001-9894-5253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Weilin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129933206","display_name":"Wenxuan Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Wenxuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081036886","display_name":"Xin Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Xin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100517197","display_name":"Yingjie Cai","orcid":"https://orcid.org/0009-0009-2013-4595"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Yingjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130198494","display_name":"Guanyi Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Guanyi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129909188","display_name":"Xu Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Xu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130089864","display_name":"Bingbing Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Bingbing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129798572","display_name":"Ying-Cong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ying-Cong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129899659","display_name":"Haoang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":13,"corresponding_author_ids":["https://openalex.org/A5109886746"],"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/T10653","display_name":"Robot Manipulation and Learning","score":0.5450000166893005,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.5450000166893005,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.19200000166893005,"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":0.09319999814033508,"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/feature","display_name":"Feature (linguistics)","score":0.6150000095367432},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5791000127792358},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.545199990272522},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.45579999685287476},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44999998807907104},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4433000087738037},{"id":"https://openalex.org/keywords/futures-studies","display_name":"Futures studies","score":0.42239999771118164},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.39340001344680786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.751800000667572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6610999703407288},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6150000095367432},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5791000127792358},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44999998807907104},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C64848388","wikidata":"https://www.wikidata.org/wiki/Q188867","display_name":"Futures studies","level":2,"score":0.42239999771118164},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.39340001344680786},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3928000032901764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37549999356269836},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3653999865055084},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.34549999237060547},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.3165000081062317},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16195","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":"doi:10.48550/arxiv.2603.16195","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16195","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6724981665611267}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"action":[1,81],"models":[2],"(VAMs)":[3],"have":[4],"emerged":[5],"as":[6,71,125],"a":[7,54,66,72,90],"promising":[8],"paradigm":[9],"for":[10,19],"robot":[11],"learning,":[12],"owing":[13],"to":[14,128,134],"their":[15],"powerful":[16],"visual":[17],"foresight":[18],"complex":[20,158],"manipulation":[21,156],"tasks.":[22],"However,":[23],"current":[24],"VAMs,":[25],"typically":[26],"relying":[27],"on":[28],"either":[29],"slow":[30],"multi-step":[31,100,117],"video":[32],"generation":[33],"or":[34],"noisy":[35,131],"one-step":[36,103,132],"feature":[37],"extraction,":[38],"cannot":[39],"simultaneously":[40],"guarantee":[41],"real-time":[42],"inference":[43],"and":[44,62,141,154],"high-fidelity":[45],"foresight.":[46],"To":[47,83],"address":[48],"this":[49,85],"limitation,":[50],"we":[51,88],"propose":[52],"S-VAM,":[53],"shortcut":[55],"video-action":[56],"model":[57,108],"that":[58,94,146],"foresees":[59],"coherent":[60],"geometric":[61],"semantic":[63],"representations":[64,77,110],"via":[65],"single":[67],"forward":[68],"pass.":[69],"Serving":[70],"stable":[73],"blueprint,":[74],"these":[75,135],"foreseen":[76],"significantly":[78],"simplify":[79],"the":[80,113,142],"prediction.":[82],"enable":[84],"efficient":[86,153],"shortcut,":[87],"introduce":[89],"novel":[91],"self-distillation":[92],"strategy":[93],"condenses":[95],"structured":[96],"generative":[97],"priors":[98],"of":[99],"denoising":[101],"into":[102],"inference.":[104],"Specifically,":[105],"vision":[106],"foundation":[107],"(VFM)":[109],"extracted":[111],"from":[112],"diffusion":[114],"model's":[115],"own":[116],"generated":[118],"videos":[119],"provide":[120],"teacher":[121],"targets.":[122,136],"Lightweight":[123],"decouplers,":[124],"students,":[126],"learn":[127],"directly":[129],"map":[130],"features":[133],"Extensive":[137],"experiments":[138],"in":[139,157],"simulation":[140],"real":[143],"world":[144],"demonstrate":[145],"our":[147],"S-VAM":[148],"outperforms":[149],"state-of-the-art":[150],"methods,":[151],"enabling":[152],"precise":[155],"environments.":[159],"Our":[160],"project":[161],"page":[162],"is":[163],"https://haodong-yan.github.io/S-VAM/":[164]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}