{"id":"https://openalex.org/W7140130500","doi":"https://doi.org/10.48550/arxiv.2603.19481","title":"Narrative Aligned Long Form Video Question Answering","display_name":"Narrative Aligned Long Form Video Question Answering","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7140130500","doi":"https://doi.org/10.48550/arxiv.2603.19481"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.19481","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19481","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.2603.19481","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130347643","display_name":"Rahul Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Rahul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059824372","display_name":"Keval Doshi","orcid":"https://orcid.org/0000-0002-2593-3320"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Doshi, Keval","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023591008","display_name":"Burak Uzkent","orcid":"https://orcid.org/0000-0002-0584-5630"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uzkent, Burak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5026277738","display_name":"Garin Kessler","orcid":"https://orcid.org/0009-0002-7292-4707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kessler, Garin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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":0.9793999791145325,"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":0.9793999791145325,"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/T10028","display_name":"Topic Modeling","score":0.008100000210106373,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0012000000569969416,"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/narrative","display_name":"Narrative","score":0.8906999826431274},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5764999985694885},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5127999782562256},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.4462999999523163},{"id":"https://openalex.org/keywords/narrative-network","display_name":"Narrative network","score":0.43320000171661377},{"id":"https://openalex.org/keywords/causal-chain","display_name":"Causal chain","score":0.3831999897956848}],"concepts":[{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.8906999826431274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7556999921798706},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5764999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5220000147819519},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5146999955177307},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.4462999999523163},{"id":"https://openalex.org/C63985673","wikidata":"https://www.wikidata.org/wiki/Q6966216","display_name":"Narrative network","level":5,"score":0.43320000171661377},{"id":"https://openalex.org/C79897977","wikidata":"https://www.wikidata.org/wiki/Q5054568","display_name":"Causal chain","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3531999886035919},{"id":"https://openalex.org/C78015137","wikidata":"https://www.wikidata.org/wiki/Q847829","display_name":"Narrative structure","level":3,"score":0.33219999074935913},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2937000095844269},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28760001063346863},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26420000195503235},{"id":"https://openalex.org/C12772571","wikidata":"https://www.wikidata.org/wiki/Q1965350","display_name":"Narrative criticism","level":4,"score":0.2615000009536743},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.19481","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19481","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.2603.19481","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19481","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5719183683395386}],"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],"progress":[1],"in":[2,61,76,131,172],"multimodal":[3],"large":[4],"language":[5],"models":[6,98],"(MLLMs)":[7],"has":[8],"led":[9],"to":[10,28,34,54,86,166],"a":[11,51,121,132],"surge":[12],"of":[13,115],"benchmarks":[14,21],"for":[15,135,155],"long-video":[16],"reasoning.":[17,138],"However,":[18],"most":[19],"existing":[20,116],"rely":[22,106],"on":[23,107,147],"localized":[24],"cues":[25],"and":[26,40,58,69,128],"fail":[27],"capture":[29],"narrative":[30,59,102,157,175],"reasoning,":[31],"the":[32,113,153],"ability":[33],"track":[35],"intentions,":[36],"connect":[37],"distant":[38],"events,":[39],"reconstruct":[41],"causal":[42],"chains":[43,127],"across":[44],"an":[45],"entire":[46],"movie.":[47],"We":[48,177],"introduce":[49],"NA-VQA,":[50],"benchmark":[52],"designed":[53],"evaluate":[55],"deep":[56],"temporal":[57],"reasoning":[60,162],"long-form":[62],"videos.":[63],"NA-VQA":[64,95,180],"contains":[65],"88":[66],"full-length":[67],"movies":[68],"4.4K":[70],"open-ended":[71],"question-answer":[72],"pairs,":[73],"each":[74],"grounded":[75],"multiple":[77],"evidence":[78],"spans":[79],"labeled":[80],"as":[81],"Short,":[82],"Medium,":[83],"or":[84],"Far":[85],"assess":[87],"long-range":[88,161],"dependencies.":[89],"By":[90],"requiring":[91,149],"generative,":[92],"multi-scene":[93],"answers,":[94],"tests":[96],"whether":[97],"can":[99],"integrate":[100],"dispersed":[101],"information":[103],"rather":[104],"than":[105],"shallow":[108],"pattern":[109],"matching.":[110],"To":[111],"address":[112],"limitations":[114],"approaches,":[117],"we":[118],"propose":[119],"Video-NaRA,":[120],"narrative-centric":[122],"framework":[123],"that":[124,142],"builds":[125],"event-level":[126],"stores":[129],"them":[130],"structured":[133],"memory":[134],"retrieval":[136],"during":[137],"Extensive":[139],"experiments":[140],"show":[141],"state-of-the-art":[143],"MLLMs":[144],"perform":[145],"poorly":[146],"questions":[148],"far-range":[150],"evidence,":[151],"highlighting":[152],"need":[154],"explicit":[156],"modeling.":[158],"Video-NaRA":[159],"improves":[160],"performance":[163],"by":[164],"up":[165],"3":[167],"percent,":[168],"demonstrating":[169],"its":[170],"effectiveness":[171],"handling":[173],"complex":[174],"structures.":[176],"will":[178],"release":[179],"upon":[181],"publication.":[182]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-24T00:00:00"}