{"id":"https://openalex.org/W7162412234","doi":"https://doi.org/10.48550/arxiv.2605.24962","title":"Tempered Self-Similarity Alignment for Physically Plausible Video Generation","display_name":"Tempered Self-Similarity Alignment for Physically Plausible Video Generation","publication_year":2026,"publication_date":"2026-05-24","ids":{"openalex":"https://openalex.org/W7162412234","doi":"https://doi.org/10.48550/arxiv.2605.24962"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.24962","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24962","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.24962","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074920600","display_name":"Manjin Kim","orcid":"https://orcid.org/0009-0004-9715-5144"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Manjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137029055","display_name":"Suha Kwak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwak, Suha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137062069","display_name":"Minsu Cho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Minsu","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":0.9341999888420105,"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":0.9341999888420105,"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/T12290","display_name":"Human Motion and Animation","score":0.019600000232458115,"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/T11448","display_name":"Face recognition and analysis","score":0.013299999758601189,"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/generative-grammar","display_name":"Generative grammar","score":0.6294000148773193},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5676000118255615},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5357999801635742},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5135999917984009},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5012999773025513},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4675999879837036},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4189999997615814},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.38580000400543213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858999729156494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.656000018119812},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6294000148773193},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5676000118255615},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5357999801635742},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5135999917984009},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5012999773025513},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.353300005197525},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2922999858856201},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28839999437332153},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27379998564720154},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.24962","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24962","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":"doi:10.48550/arxiv.2605.24962","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.24962","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.582696795463562}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"remarkable":[1],"advances":[2],"in":[3,36,134],"video":[4,45,104,151],"generative":[5,46,105],"models,":[6],"they":[7],"still":[8],"struggle":[9],"to":[10,107],"generate":[11],"physically":[12,149],"realistic":[13,150],"videos,":[14],"frequently":[15],"exhibiting":[16],"appearance":[17],"drift,":[18],"implausible":[19],"motion,":[20],"and":[21,56,79,101,126],"temporal":[22],"inconsistencies.":[23],"In":[24],"this":[25,29,84],"work,":[26],"we":[27,87],"address":[28],"limitation":[30],"by":[31],"transferring":[32,145],"relational":[33,60,85,146],"knowledge":[34,147],"encoded":[35],"spatio-temporal":[37],"self-similarity":[38],"(STSS)":[39],"from":[40],"visual":[41,116],"foundation":[42,117],"models":[43],"into":[44,97],"models.":[47],"STSS":[48,96],"represents":[49],"pairwise":[50],"similarities":[51],"among":[52],"features":[53],"across":[54,137],"space":[55],"time,":[57],"revealing":[58],"the":[59,103,115,142],"structure":[61],"of":[62,114,144],"how":[63],"objects":[64],"interact":[65],"with":[66,112],"other":[67],"entities":[68],"throughout":[69],"a":[70],"video,":[71],"effectively":[72],"capturing":[73],"real-world":[74],"dynamics,":[75],"including":[76],"object":[77],"motion":[78],"semantic":[80],"transformations.":[81],"To":[82],"transfer":[83],"knowledge,":[86],"propose":[88],"Tempered":[89],"Self-similarity":[90],"Alignment":[91],"(TSA)":[92],"loss,":[93],"which":[94],"transforms":[95],"probabilistic":[98],"correspondence":[99,110],"distributions":[100,111],"trains":[102],"model":[106,118],"align":[108],"its":[109],"those":[113],"on":[119,124],"dynamically":[120],"changing":[121],"regions.":[122],"Evaluated":[123],"VideoPhy":[125],"VideoPhy2":[127],"benchmarks,":[128],"our":[129],"method":[130],"demonstrates":[131],"substantial":[132],"improvements":[133],"physical":[135],"plausibility":[136],"diverse":[138],"interaction":[139],"scenarios,":[140],"validating":[141],"effectiveness":[143],"for":[148],"generation.":[152]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}