{"id":"https://openalex.org/W7138930316","doi":"https://doi.org/10.48550/arxiv.2603.17693","title":"Learning Transferable Temporal Primitives for Video Reasoning via Synthetic Videos","display_name":"Learning Transferable Temporal Primitives for Video Reasoning via Synthetic Videos","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7138930316","doi":"https://doi.org/10.48550/arxiv.2603.17693"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17693","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.17693","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130088362","display_name":"Songtao Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Songtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129836646","display_name":"Sibo Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Sibo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130122574","display_name":"Chenyi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Chenyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130070981","display_name":"Yuan Wang (15109820)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129813315","display_name":"Ruizhe Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ruizhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059748327","display_name":"Tongkun Guan","orcid":"https://orcid.org/0000-0003-3346-8315"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Tongkun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130211023","display_name":"Ruilin Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Ruilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129845514","display_name":"Yan  (1978 - ) Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120698113","display_name":"Zhiheng Tang","orcid":"https://orcid.org/0000-0002-3744-2254"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Zhihang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130018598","display_name":"Yuchong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yuchong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130127976","display_name":"Hang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Hang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130128384","display_name":"Zhibo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhibo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130134035","display_name":"Shuai Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129961075","display_name":"Junyang Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Junyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130160837","display_name":"Zuozhu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zuozhu","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.883400022983551,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.883400022983551,"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":0.04010000079870224,"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":0.0272000003606081,"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/motion","display_name":"Motion (physics)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5356000065803528},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.49799999594688416},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4862000048160553},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.45239999890327454},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4505000114440918},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.43810001015663147},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4165000021457672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8095999956130981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6327999830245972},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5356000065803528},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.49799999594688416},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.45239999890327454},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3767000138759613},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3652999997138977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C25016198","wikidata":"https://www.wikidata.org/wiki/Q781833","display_name":"Temporal logic","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17693","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17693","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.720724880695343}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"transition":[1],"from":[2,13,53,118,211],"image":[3],"to":[4,11,17,38,125,194,215],"video":[5,155,177,225,227],"understanding":[6,102,131],"requires":[7],"vision-language":[8],"models":[9,69,93],"(VLMs)":[10],"shift":[12],"recognizing":[14],"static":[15],"patterns":[16,214],"reasoning":[18],"over":[19],"temporal":[20,60,75,94,101,130,171,196,228],"dynamics":[21],"such":[22,77,198],"as":[23,78,199],"motion":[24,80],"trajectories,":[25],"speed":[26],"changes,":[27],"and":[28,62,106,138,145,175,205],"state":[29,107],"transitions.":[30],"Yet":[31],"current":[32],"post-training":[33,89],"methods":[34],"fall":[35],"short":[36],"due":[37],"two":[39],"critical":[40],"limitations:":[41],"(1)":[42],"existing":[43],"datasets":[44],"often":[45],"lack":[46],"temporal-centricity,":[47],"where":[48],"answers":[49],"can":[50],"be":[51],"inferred":[52],"isolated":[54],"keyframes":[55],"rather":[56],"than":[57],"requiring":[58],"holistic":[59],"integration;":[61],"(2)":[63],"training":[64,158],"data":[65,234],"generated":[66,120],"by":[67,202],"proprietary":[68],"contains":[70],"systematic":[71],"errors":[72],"in":[73],"fundamental":[74,97,195],"perception,":[76],"confusing":[79],"directions":[81],"or":[82],"misjudging":[83],"speeds.":[84],"We":[85,128,191],"introduce":[86],"SynRL,":[87],"a":[88,221,236],"framework":[90],"that":[91,113,208],"teaches":[92],"primitives,":[95,116,141],"the":[96],"building":[98],"blocks":[99],"of":[100],"including":[103],"direction,":[104],"speed,":[105],"tracking.":[108],"Our":[109],"key":[110],"insight":[111],"is":[112],"these":[114],"abstract":[115,212],"learned":[117],"programmatically":[119],"synthetic":[121,182,213,233],"videos,":[122],"transfer":[123,209],"effectively":[124,210],"real-world":[126,189,217],"scenarios.":[127,218],"decompose":[129],"into":[132],"short-term":[133],"perceptual":[134],"primitives":[135],"(speed,":[136],"direction)":[137],"long-term":[139],"cognitive":[140],"constructing":[142],"7.7K":[143,181],"CoT":[144,183],"7K":[146],"RL":[147],"samples":[148,184],"with":[149,187],"ground-truth":[150],"frame-level":[151],"annotations":[152],"through":[153,230],"code-based":[154],"generation.":[156],"Despite":[157],"on":[159],"simple":[160],"geometric":[161],"shapes,":[162],"SynRL":[163],"achieves":[164],"substantial":[165],"improvements":[166],"across":[167],"15":[168],"benchmarks":[169],"spanning":[170],"grounding,":[172],"complex":[173,216],"reasoning,":[174],"general":[176],"understanding.":[178],"Remarkably,":[179],"our":[180],"outperform":[185],"Video-R1":[186],"165K":[188],"samples.":[190],"attribute":[192],"this":[193],"skills,":[197],"tracking":[200],"frame":[201,203],"changes":[204],"comparing":[206],"velocity,":[207],"This":[219],"establishes":[220],"new":[222],"paradigm":[223],"for":[224],"post-training:":[226],"learning":[229],"carefully":[231],"designed":[232],"provides":[235],"more":[237],"cost":[238],"efficient":[239],"scaling":[240],"path.":[241]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-20T00:00:00"}