{"id":"https://openalex.org/W7134191392","doi":"https://doi.org/10.1109/bigdata66926.2025.11401853","title":"AVATAAR: Agentic Video Answering via Temporal Adaptive Alignment and Reasoning","display_name":"AVATAAR: Agentic Video Answering via Temporal Adaptive Alignment and Reasoning","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7134191392","doi":"https://doi.org/10.1109/bigdata66926.2025.11401853"},"language":null,"primary_location":{"id":"doi:10.1109/bigdata66926.2025.11401853","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata66926.2025.11401853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.15578","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114127655","display_name":"Fang-Chun Yeh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096602","display_name":"Global College","ror":"https://ror.org/00q24dt49","country_code":"CY","type":"education","lineage":["https://openalex.org/I4210096602"]}],"countries":["CY"],"is_corresponding":true,"raw_author_name":"Fang-Chun Yeh","raw_affiliation_strings":["S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America"],"affiliations":[{"raw_affiliation_string":"S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America","institution_ids":["https://openalex.org/I4210096602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111130559","display_name":"Urjitkumar Patel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096602","display_name":"Global College","ror":"https://ror.org/00q24dt49","country_code":"CY","type":"education","lineage":["https://openalex.org/I4210096602"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Urjitkumar Patel","raw_affiliation_strings":["S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America"],"affiliations":[{"raw_affiliation_string":"S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America","institution_ids":["https://openalex.org/I4210096602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093940847","display_name":"Chinmay Gondhalekar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210096602","display_name":"Global College","ror":"https://ror.org/00q24dt49","country_code":"CY","type":"education","lineage":["https://openalex.org/I4210096602"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Chinmay Gondhalekar","raw_affiliation_strings":["S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America"],"affiliations":[{"raw_affiliation_string":"S&#x0026;P Global Inc.,Commercial Data Science,New York,United States Of America","institution_ids":["https://openalex.org/I4210096602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114127655"],"corresponding_institution_ids":["https://openalex.org/I4210096602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72559289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5255","last_page":"5262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9115999937057495,"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":0.9115999937057495,"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/T11439","display_name":"Video Analysis and Summarization","score":0.017999999225139618,"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/T12031","display_name":"Speech and dialogue systems","score":0.009100000374019146,"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/action","display_name":"Action (physics)","score":0.34060001373291016},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3212999999523163},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2687000036239624},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.2549000084400177},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.23759999871253967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6660000085830688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5521000027656555},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.30709999799728394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3025999963283539},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.23759999871253967},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.23749999701976776}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata66926.2025.11401853","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata66926.2025.11401853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2511.15578","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2511.15578","pdf_url":"https://arxiv.org/pdf/2511.15578","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.15578","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2511.15578","pdf_url":"https://arxiv.org/pdf/2511.15578","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.47016575932502747,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7134191392.pdf","grobid_xml":"https://content.openalex.org/works/W7134191392.grobid-xml"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W3099700870","https://openalex.org/W3175961224","https://openalex.org/W4382202923","https://openalex.org/W4391877130","https://openalex.org/W4406458098"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,89,93,99,116,156,160],"increasing":[2],"prevalence":[3],"of":[4,129],"video":[5,64,174],"content,":[6],"effectively":[7],"understanding":[8,43,175],"and":[9,44,56,62,73,83,92,110,142,192],"answering":[10],"questions":[11],"about":[12],"long":[13],"form":[14],"videos":[15],"has":[16],"become":[17],"essential":[18],"for":[19,165,183],"numerous":[20],"applications.":[21],"Although":[22],"large":[23],"vision":[24],"language":[25],"models":[26],"(LVLMs)":[27],"have":[28],"enhanced":[29],"performance,":[30,158],"they":[31],"often":[32],"face":[33],"challenges":[34],"with":[35,67,159],"nuanced":[36],"queries":[37],"that":[38,59,150],"demand":[39],"both":[40],"a":[41,54,68,74,79,85,124,180],"comprehensive":[42],"detailed":[45],"analysis.":[46],"To":[47],"overcome":[48],"these":[49],"obstacles,":[50],"we":[51],"introduce":[52],"AVATAAR,":[53],"modular":[55],"interpretable":[57],"framework":[58],"combines":[60],"global":[61,81],"local":[63],"context,":[65],"along":[66],"Pre":[69,94],"Retrieval":[70,95],"Thinking":[71,96],"Agent":[72],"Rethink":[75,90],"Module.":[76],"AVATAAR":[77,119,178],"creates":[78],"persistent":[80],"summary":[82],"establishes":[84],"feedback":[86,161],"loop":[87,162],"between":[88],"Module":[91],"Agent,":[97],"allowing":[98],"system":[100],"to":[101,155],"refine":[102],"its":[103],"retrieval":[104],"strategies":[105],"based":[106],"on":[107],"partial":[108],"answers":[109],"replicate":[111],"human-like":[112],"iterative":[113],"reasoning.":[114],"On":[115],"CinePile":[117],"benchmark,":[118],"demonstrates":[120],"significant":[121],"improvements":[122],"over":[123],"baseline,":[125],"achieving":[126],"relative":[127],"gains":[128],"+5.6%":[130],"in":[131,135,139,144,172],"temporal":[132],"reasoning,":[133],"+5%":[134],"technical":[136],"queries,":[137],"+8%":[138],"theme-based":[140],"questions,":[141],"+8.2%":[143],"narrative":[145],"comprehension.":[146],"Our":[147],"experiments":[148],"confirm":[149],"each":[151],"module":[152],"contributes":[153],"positively":[154],"overall":[157],"being":[163],"crucial":[164],"adaptability.":[166],"These":[167],"findings":[168],"highlight":[169],"AVATAAR's":[170],"effectiveness":[171],"enhancing":[173],"capabilities.":[176],"Ultimately,":[177],"presents":[179],"scalable":[181],"solution":[182],"long-form":[184],"Video":[185],"Question":[186],"Answering":[187],"(QA),":[188],"merging":[189],"accuracy,":[190],"interpretability,":[191],"extensibility.":[193]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2026-03-09T00:00:00"}
