{"id":"https://openalex.org/W4415709553","doi":"https://doi.org/10.1109/icme59968.2025.11210173","title":"Causal Intervention with Active Learning for Large Vision-Language Models in Egocentric Contexts","display_name":"Causal Intervention with Active Learning for Large Vision-Language Models in Egocentric Contexts","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415709553","doi":"https://doi.org/10.1109/icme59968.2025.11210173"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11210173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11210173","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wenxin Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Meng","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043867916","display_name":"Shenshen Li","orcid":"https://orcid.org/0000-0002-6340-012X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenshen Li","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436085","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0003-1228-6758"},"institutions":[{"id":"https://openalex.org/I4210155268","display_name":"Salesforce (United States)","ror":"https://ror.org/057315g56","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Salesforce AI Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Salesforce AI Research","institution_ids":["https://openalex.org/I4210155268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005698391","display_name":"Hao Yang","orcid":"https://orcid.org/0000-0001-8506-7295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Yang","raw_affiliation_strings":["Meituan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120312334","display_name":"Chong Peng","orcid":"https://orcid.org/0000-0001-8617-4105"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chong Peng","raw_affiliation_strings":["Meituan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772740","display_name":"Yan Peng","orcid":"https://orcid.org/0000-0003-1312-9527"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng Yan","raw_affiliation_strings":["Meituan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009074046","display_name":"Xing Xu","orcid":"https://orcid.org/0000-0001-5685-3123"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.925000011920929,"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":0.925000011920929,"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":0.015200000256299973,"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":0.012799999676644802,"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/intervention","display_name":"Intervention (counseling)","score":0.5774999856948853},{"id":"https://openalex.org/keywords/certainty","display_name":"Certainty","score":0.538100004196167},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.424699991941452},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.41269999742507935},{"id":"https://openalex.org/keywords/conjunction","display_name":"Conjunction (astronomy)","score":0.38960000872612},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.36320000886917114},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3619000017642975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5785999894142151},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.5774999856948853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5476999878883362},{"id":"https://openalex.org/C7493553","wikidata":"https://www.wikidata.org/wiki/Q1520777","display_name":"Certainty","level":2,"score":0.538100004196167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.424699991941452},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.39649999141693115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3953000009059906},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.36320000886917114},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3619000017642975},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3416999876499176},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C2982912361","wikidata":"https://www.wikidata.org/wiki/Q1851867","display_name":"Mental model","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26750001311302185}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11210173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11210173","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W3205786327","https://openalex.org/W4386038408","https://openalex.org/W4387969779","https://openalex.org/W4389518829","https://openalex.org/W4391287688","https://openalex.org/W4393148792","https://openalex.org/W4402727669","https://openalex.org/W4402772286","https://openalex.org/W4402781634","https://openalex.org/W4403791468","https://openalex.org/W4404575065","https://openalex.org/W4404612908","https://openalex.org/W4408841099"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,32,94,139],"Large":[3],"Vision-Language":[4],"Models":[5],"(LVLMs)":[6],"have":[7],"attracted":[8],"considerable":[9],"attention":[10],"due":[11],"to":[12,54,78,85,89,135],"their":[13],"impressive":[14],"performance":[15],"across":[16],"various":[17],"downstream":[18],"tasks.":[19],"However,":[20],"these":[21,40],"tasks":[22],"predominantly":[23],"emphasize":[24],"third-person":[25],"perspectives":[26],"and":[27,80,113,137],"LVLMs":[28,76,108],"demonstrate":[29,125],"inadequate":[30],"capability":[31],"reasoning":[33,58],"from":[34],"a":[35,99],"first-person":[36,57],"perspective.":[37],"To":[38],"mitigate":[39],"limitations,":[41],"we":[42],"introduce":[43],"Causal":[44,101],"Intervention":[45,102],"with":[46,96],"Active":[47,68],"Learning":[48],"(CIAL),":[49],"an":[50,67],"innovative":[51],"approach":[52],"designed":[53],"augment":[55],"the":[56,91,97,122,132],"capabilities":[59],"of":[60],"LVLMs.":[61],"Specifically,":[62],"our":[63,127],"method":[64,129],"first":[65],"incorporates":[66],"Learning-driven":[69],"Knowledge":[70],"Extraction":[71],"(ALKE)":[72],"scheme,":[73],"which":[74],"utilizes":[75],"themselves":[77],"automatically":[79],"autonomously":[81],"acquire":[82],"knowledge":[83,112],"related":[84],"egocentric":[86,140],"perspectives.":[87],"Then,":[88],"optimize":[90],"model\u2019s":[92],"response":[93],"conjunction":[95],"scene,":[98],"Knowledge-guided":[100],"(KCI)":[103],"module":[104],"is":[105,145],"employed,":[106],"thereby":[107],"can":[109],"integrate":[110],"both":[111],"certainty":[114],"scores":[115],"for":[116],"inference.":[117],"Comprehensive":[118],"experiments":[119],"conducted":[120],"on":[121],"EgoThink":[123],"benchmark":[124],"that":[126],"CIAL":[128],"significantly":[130],"improves":[131],"models\u2019":[133],"ability":[134],"understand":[136],"reason":[138],"contexts.":[141],"Our":[142],"anonymous":[143],"code":[144],"available":[146],"at":[147],"https://github.com/running-alpaca/CIAL/.":[148]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-30T00:00:00"}