{"id":"https://openalex.org/W7148365258","doi":"https://doi.org/10.48550/arxiv.2604.00696","title":"TTA-Vid: Generalized Test-Time Adaptation for Video Reasoning","display_name":"TTA-Vid: Generalized Test-Time Adaptation for Video Reasoning","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148365258","doi":"https://doi.org/10.48550/arxiv.2604.00696"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.00696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00696","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.2604.00696","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004782135","display_name":"Soumya Jahagirdar","orcid":"https://orcid.org/0000-0002-3460-9151"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jahagirdar, Soumya Shamarao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061048633","display_name":"Edson Araujo","orcid":"https://orcid.org/0000-0003-0585-5473"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Araujo, Edson","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132815753","display_name":"Anna Kukleva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kukleva, Anna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132798071","display_name":"M. Jehanzeb Mirza","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mirza, M. Jehanzeb","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045247662","display_name":"Saurabhchand Bhati","orcid":"https://orcid.org/0000-0001-6477-3895"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhati, Saurabhchand","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132734393","display_name":"Samuel Thomas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas, Samuel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003725957","display_name":"Brian Kingsbury","orcid":"https://orcid.org/0000-0002-1343-6837"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kingsbury, Brian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132792222","display_name":"Rogerio Feris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feris, Rogerio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132824681","display_name":"James R. Glass","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Glass, James R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5121265388","display_name":"Hilde Kuehne","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuehne, Hilde","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"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":0.7781000137329102,"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":0.7781000137329102,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.07890000194311142,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.03060000017285347,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6873999834060669},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6345999836921692},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6017000079154968},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5824999809265137},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5299999713897705},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4415000081062317},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41290000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7773000001907349},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6873999834060669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6643999814987183},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6345999836921692},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6017000079154968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5971999764442444},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5824999809265137},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4415000081062317},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2919999957084656},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.00696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00696","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.2604.00696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00696","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"video":[1,59,71,199],"reasoning":[2,87,200],"models":[3],"have":[4],"shown":[5],"strong":[6],"results":[7],"on":[8,16,47,91,122,211],"temporal":[9,223],"and":[10,20,29,144,202],"multimodal":[11,224],"understanding,":[12],"yet":[13],"they":[14],"depend":[15],"large-scale":[17,212],"supervised":[18],"data":[19,49],"multi-stage":[21],"training":[22,164],"pipelines,":[23],"making":[24],"them":[25],"costly":[26],"to":[27,31,33,50,57,111,136,140,179,205],"train":[28],"difficult":[30],"adapt":[32],"new":[34],"domains.":[35],"In":[36],"this":[37],"work,":[38],"we":[39,167],"leverage":[40],"the":[41,113,118,141,149,185,216],"paradigm":[42],"of":[43,218],"Test-Time":[44],"Reinforcement":[45],"Learning":[46],"video-language":[48],"allow":[51],"for":[52,70,173,222],"adapting":[53],"a":[54,81,98,123,128,132,169],"pretrained":[55],"model":[56,120],"incoming":[58],"samples":[60],"at":[61,88,138,153],"test-time":[62,68,82,139,219],"without":[63],"explicit":[64],"labels.":[65],"The":[66],"proposed":[67],"adaptation":[69,83,150],"approach":[72],"(TTA-Vid)":[73],"combines":[74],"two":[75],"components":[76],"that":[77,84,117,177,192],"work":[78],"simultaneously:":[79],"(1)":[80],"performs":[85],"step-by-step":[86],"inference":[89],"time":[90],"multiple":[92],"frame":[93,105,175],"subsets.":[94],"We":[95],"then":[96],"use":[97],"batch-aware":[99],"frequency-based":[100],"reward":[101,187],"computed":[102],"across":[103,146,197],"different":[104],"subsets":[106],"as":[107],"pseudo":[108],"ground":[109],"truth":[110],"update":[112],"model.":[114],"It":[115],"shows":[116,191],"resulting":[119],"trained":[121,210],"single":[124,129],"batch":[125],"or":[126,162],"even":[127,145],"sample":[130],"from":[131],"dataset,":[133],"is":[134,203],"able":[135,204],"generalize":[137],"whole":[142],"dataset":[143],"datasets.":[147],"Because":[148],"occurs":[151],"entirely":[152],"test":[154],"time,":[155],"our":[156],"method":[157],"requires":[158],"no":[159],"ground-truth":[160],"annotations":[161],"dedicated":[163],"splits.":[165],"Additionally,":[166],"propose":[168],"multi-armed":[170],"bandit":[171],"strategy":[172],"adaptive":[174],"selection":[176],"learns":[178],"prioritize":[180],"informative":[181],"frames,":[182],"guided":[183],"by":[184],"same":[186],"formulation.":[188],"Our":[189],"evaluation":[190],"TTA-Vid":[193],"yields":[194],"consistent":[195],"improvements":[196],"various":[198],"tasks":[201],"outperform":[206],"current":[207],"state-of-the-art":[208],"methods":[209],"data.":[213],"This":[214],"highlights":[215],"potential":[217],"reinforcement":[220],"learning":[221],"understanding.":[225]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-03T00:00:00"}
