{"id":"https://openalex.org/W4416750495","doi":"https://doi.org/10.1109/iros60139.2025.11247438","title":"EfficientEQA: An Efficient Approach to Open-Vocabulary Embodied Question Answering","display_name":"EfficientEQA: An Efficient Approach to Open-Vocabulary Embodied Question Answering","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416750495","doi":"https://doi.org/10.1109/iros60139.2025.11247438"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":"https://openalex.org/A5101761689","display_name":"Kai Cheng","orcid":"https://orcid.org/0000-0002-4340-8482"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Cheng","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102730109","display_name":"Zhengyuan Li","orcid":"https://orcid.org/0000-0002-1515-4008"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengyuan Li","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108313742","display_name":"Xingpeng Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingpeng Sun","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076467173","display_name":"Byung\u2010Cheol Min","orcid":"https://orcid.org/0000-0001-6458-4365"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byung-Cheol Min","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039563144","display_name":"Amrit Singh Bedi","orcid":"https://orcid.org/0000-0002-8807-2695"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amrit Singh Bedi","raw_affiliation_strings":["University of Central Florida,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida,USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058453308","display_name":"Aniket Bera","orcid":"https://orcid.org/0000-0002-0182-6985"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aniket Bera","raw_affiliation_strings":["Purdue University,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.86366594,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"20357","last_page":"20364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.987500011920929,"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":0.987500011920929,"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":0.0027000000700354576,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/flagging","display_name":"Flagging","score":0.7851999998092651},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7541999816894531},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.6486999988555908},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6391000151634216},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6254000067710876},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5414999723434448},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4230000078678131},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.3862999975681305}],"concepts":[{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.7851999998092651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7666000127792358},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7541999816894531},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.6486999988555908},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6391000151634216},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6254000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.559499979019165},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4230000078678131},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3813999891281128},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3384000062942505},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28999999165534973},{"id":"https://openalex.org/C62360110","wikidata":"https://www.wikidata.org/wiki/Q96777007","display_name":"Circumscription","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27070000767707825},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.2587999999523163},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1933349210","https://openalex.org/W2107667896","https://openalex.org/W2529436507","https://openalex.org/W2930283066","https://openalex.org/W2950697717","https://openalex.org/W2962684798","https://openalex.org/W2964138343","https://openalex.org/W2964487155","https://openalex.org/W4205261319","https://openalex.org/W4290994954","https://openalex.org/W4313026212","https://openalex.org/W4383097638","https://openalex.org/W4383108296","https://openalex.org/W4383108895","https://openalex.org/W4386071473","https://openalex.org/W4386083015","https://openalex.org/W4389518686","https://openalex.org/W4393154152","https://openalex.org/W4401417048","https://openalex.org/W4401417061","https://openalex.org/W4402353981","https://openalex.org/W4402353987","https://openalex.org/W4402716288","https://openalex.org/W4402727730","https://openalex.org/W4402727764","https://openalex.org/W4402776116","https://openalex.org/W4403081466","https://openalex.org/W4404782982","https://openalex.org/W4405785122","https://openalex.org/W4405785171","https://openalex.org/W4405786470"],"related_works":[],"abstract_inverted_index":{"Embodied":[0],"Question":[1],"Answering":[2],"(EQA)":[3],"is":[4,189],"an":[5],"essential":[6],"yet":[7],"challenging":[8],"task":[9],"for":[10,20,145],"robot":[11,52],"assistants.":[12],"Large":[13],"vision-language":[14],"models":[15],"(VLMs)":[16],"have":[17],"shown":[18],"promise":[19],"EQA,":[21],"but":[22],"existing":[23],"approaches":[24],"either":[25],"treat":[26],"it":[27],"as":[28,127],"static":[29],"video":[30],"question":[31],"answering":[32],"without":[33,160],"active":[34],"exploration":[35,76,182],"or":[36],"restrict":[37],"answers":[38,59],"to":[39,99,104,109,119,129,148],"a":[40,51,70,96,115,140],"closed":[41],"set":[42],"of":[43],"choices.":[44,164],"These":[45],"limitations":[46],"hinder":[47],"real-world":[48],"applicability,":[49],"where":[50],"must":[53],"explore":[54],"efficiently":[55],"and":[56,138,177],"provide":[57],"accurate":[58],"in":[60],"open-vocabulary":[61],"settings.":[62],"To":[63],"overcome":[64],"these":[65],"challenges,":[66],"we":[67],"introduce":[68],"EfficientEQA,":[69],"novel":[71],"framework":[72],"that":[73,169],"couples":[74],"efficient":[75],"with":[77,91],"free-form":[78],"answer":[79,149,175],"generation.":[80],"EfficientEQA":[81,170],"features":[82],"three":[83],"key":[84],"innovations:":[85],"(1)":[86],"Semantic-Value-Weighted":[87],"Frontier":[88],"Exploration":[89],"(SFE)":[90],"Verbalized":[92],"Confidence":[93],"(VC)":[94],"from":[95,155],"black-box":[97],"VLM":[98,147],"prioritize":[100],"semantically":[101],"important":[102],"areas":[103],"explore,":[105],"enabling":[106],"the":[107,132,146,156],"agent":[108,133],"gather":[110],"relevant":[111,125],"information":[112],"faster;":[113],"(2)":[114],"BLIP":[116],"relevancy-based":[117],"mechanism":[118],"stop":[120],"adaptively":[121],"by":[122],"flagging":[123],"highly":[124],"observations":[126],"outliers":[128],"indicate":[130],"whether":[131],"has":[134],"collected":[135],"enough":[136],"information;":[137],"(3)":[139],"Retrieval-Augmented":[141],"Generation":[142],"(RAG)":[143],"method":[144],"accurately":[150],"based":[151],"on":[152,162],"pertinent":[153],"images":[154],"agent\u2019s":[157],"observation":[158],"history":[159],"relying":[161],"predefined":[163],"Our":[165,187],"experimental":[166],"results":[167],"show":[168],"achieves":[171],"over":[172,179],"15%":[173],"higher":[174],"accuracy":[176],"requires":[178],"20%":[180],"fewer":[181],"steps":[183],"than":[184],"state-of-the-art":[185],"methods.":[186],"code":[188],"available":[190],"at:":[191],"https://github.com/chengkaiAcademyCity/EfficientEQA":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-28T00:00:00"}