{"id":"https://openalex.org/W7148908860","doi":"https://doi.org/10.48550/arxiv.2604.01824","title":"STRIVE: Structured Spatiotemporal Exploration for Reinforcement Learning in Video Question Answering","display_name":"STRIVE: Structured Spatiotemporal Exploration for Reinforcement Learning in Video Question Answering","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148908860","doi":"https://doi.org/10.48550/arxiv.2604.01824"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01824","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01824","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.2604.01824","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026496713","display_name":"Emad Bahrami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bahrami, Emad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019386224","display_name":"Olga Zatsarynna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zatsarynna, Olga","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132881210","display_name":"Parth Pathak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pathak, Parth","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069905715","display_name":"Sunando Sengupta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sengupta, Sunando","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Gall, Juergen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gall, Juergen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031986521","display_name":"Mohsen Fayyaz","orcid":"https://orcid.org/0000-0001-5254-3128"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fayyaz, Mohsen","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":0.9941999912261963,"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":0.9941999912261963,"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":0.0010999999940395355,"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/T10028","display_name":"Topic Modeling","score":0.0007999999797903001,"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":0.8173999786376953},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6644999980926514},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.517799973487854},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.5026999711990356},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.444599986076355},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.36419999599456787},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.3634999990463257},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.3027999997138977}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8173999786376953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7422000169754028},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6644999980926514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874999761581421},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.5026999711990356},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.444599986076355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43070000410079956},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C2779321571","wikidata":"https://www.wikidata.org/wiki/Q7936605","display_name":"Visual learning","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01824","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01824","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.2604.01824","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01824","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/4","score":0.4924359619617462,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"introduce":[1,103],"STRIVE":[2,49,84],"(SpatioTemporal":[3],"Reinforcement":[4],"with":[5],"Importance-aware":[6],"Variant":[7],"Exploration),":[8],"a":[9,134,176],"structured":[10,81,172],"reinforcement":[11,158,182],"learning":[12,159,183],"framework":[13],"for":[14,179],"video":[15,61,142,186],"question":[16,116],"answering.":[17],"While":[18],"group-based":[19],"policy":[20,94],"optimization":[21],"methods":[22],"have":[23],"shown":[24],"promise":[25],"in":[26],"large":[27,163],"multimodal":[28,164,181],"models,":[29],"they":[30],"often":[31],"suffer":[32],"from":[33],"low":[34],"reward":[35,86],"variance":[36],"when":[37],"responses":[38],"exhibit":[39],"similar":[40],"correctness,":[41],"leading":[42],"to":[43,80,113,133],"weak":[44],"or":[45],"unstable":[46],"advantage":[47],"estimates.":[48],"addresses":[50],"this":[51],"limitation":[52],"by":[53],"constructing":[54],"multiple":[55,162],"spatiotemporal":[56,136,173],"variants":[57],"of":[58,171],"each":[59],"input":[60,115],"and":[62,70,88,92,151,184],"performing":[63],"joint":[64],"normalization":[65],"across":[66,126,161],"both":[67],"textual":[68],"generations":[69],"visual":[71,82,128],"variants.":[72],"By":[73],"expanding":[74],"group":[75],"comparisons":[76],"beyond":[77],"linguistic":[78],"diversity":[79],"perturbations,":[83],"enriches":[85],"signals":[87],"promotes":[89],"more":[90],"stable":[91],"informative":[93],"updates.":[95],"To":[96],"ensure":[97],"exploration":[98,174],"remains":[99],"semantically":[100],"grounded,":[101],"we":[102],"an":[104],"importance-aware":[105],"sampling":[106],"mechanism":[107,178],"that":[108],"prioritizes":[109],"frames":[110],"most":[111],"relevant":[112],"the":[114,169],"while":[117],"preserving":[118],"temporal":[119],"coverage.":[120],"This":[121],"design":[122],"encourages":[123],"robust":[124],"reasoning":[125,143,187],"complementary":[127],"perspectives":[129],"rather":[130],"than":[131],"overfitting":[132],"single":[135],"configuration.":[137],"Experiments":[138],"on":[139],"six":[140],"challenging":[141],"benchmarks":[144],"including":[145],"VideoMME,":[146],"TempCompass,":[147],"VideoMMMU,":[148],"MMVU,":[149],"VSI-Bench,":[150],"PerceptionTest":[152],"demonstrate":[153],"consistent":[154],"improvements":[155],"over":[156],"strong":[157],"baselines":[160],"models.":[165],"Our":[166],"results":[167],"highlight":[168],"role":[170],"as":[175],"principled":[177],"stabilizing":[180],"improving":[185],"performance.":[188]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-04T00:00:00"}