{"id":"https://openalex.org/W4416750309","doi":"https://doi.org/10.1109/iros60139.2025.11247137","title":"Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering","display_name":"Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416750309","doi":"https://doi.org/10.1109/iros60139.2025.11247137"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247137","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":"article","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/A5028418159","display_name":"Vishnu Sashank Dorbala","orcid":"https://orcid.org/0000-0001-5697-5219"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vishnu Sashank Dorbala","raw_affiliation_strings":["University of Maryland,College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland,College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072713291","display_name":"Prasoon Goyal","orcid":"https://orcid.org/0000-0003-3121-1241"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasoon Goyal","raw_affiliation_strings":["Amazon AGI"],"affiliations":[{"raw_affiliation_string":"Amazon AGI","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018704921","display_name":"Robinson Piramuthu","orcid":"https://orcid.org/0000-0002-1767-8382"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robinson Piramuthu","raw_affiliation_strings":["Amazon AGI"],"affiliations":[{"raw_affiliation_string":"Amazon AGI","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058476987","display_name":"Michael Johnston","orcid":"https://orcid.org/0000-0001-9869-6357"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Johnston","raw_affiliation_strings":["Amazon AGI"],"affiliations":[{"raw_affiliation_string":"Amazon AGI","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081649915","display_name":"Reza Ghanadan","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza Ghanadan","raw_affiliation_strings":["University of Maryland,College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland,College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004194238","display_name":"Dinesh Manocha","orcid":"https://orcid.org/0000-0001-7047-9801"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dinesh Manocha","raw_affiliation_strings":["University of Maryland,College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland,College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5028418159"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40276355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"18430","last_page":"18437"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.6995999813079834,"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":0.6995999813079834,"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":0.06379999965429306,"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/T12031","display_name":"Speech and dialogue systems","score":0.05350000038743019,"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/situational-ethics","display_name":"Situational ethics","score":0.8661999702453613},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.7091000080108643},{"id":"https://openalex.org/keywords/situation-awareness","display_name":"Situation awareness","score":0.5220000147819519},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5199999809265137},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5024999976158142},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4869000017642975},{"id":"https://openalex.org/keywords/common-ground","display_name":"Common ground","score":0.3691999912261963},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.34940001368522644}],"concepts":[{"id":"https://openalex.org/C9114305","wikidata":"https://www.wikidata.org/wiki/Q1428317","display_name":"Situational ethics","level":2,"score":0.8661999702453613},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.7091000080108643},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6758999824523926},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.5220000147819519},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5199999809265137},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3849000036716461},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38089999556541443},{"id":"https://openalex.org/C2777877512","wikidata":"https://www.wikidata.org/wiki/Q1116097","display_name":"Common ground","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3452000021934509},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3330000042915344},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C14911803","wikidata":"https://www.wikidata.org/wiki/Q7532148","display_name":"Situation analysis","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.25679999589920044},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247137","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2799002257","https://openalex.org/W2950697717","https://openalex.org/W2962684798","https://openalex.org/W2964487155","https://openalex.org/W3136858040","https://openalex.org/W3199446738","https://openalex.org/W3204868383","https://openalex.org/W4207072548","https://openalex.org/W4312989333","https://openalex.org/W4324125087","https://openalex.org/W4383109113","https://openalex.org/W4385571689","https://openalex.org/W4390874280","https://openalex.org/W4393154152"],"related_works":[],"abstract_inverted_index":{"We":[0,264],"present":[1,257],"and":[2,31,67,99,252],"tackle":[3],"the":[4,35,38,45,55,112,154,167,196,233,240,247,254,271],"problem":[5],"of":[6,37,135,164,235,249,274],"Embodied":[7],"Question":[8],"Answering":[9],"(EQA)":[10],"with":[11,166],"Situational":[12],"Queries":[13],"(S-EQA)":[14],"in":[15,111,152,202,214,221,246],"a":[16,69,83,124,132,161,215,226,258],"household":[17],"environment.":[18],"Unlike":[19],"prior":[20],"EQA":[21,245],"work":[22,242],"tackling":[23],"simple":[24],"queries":[25,41,98,251],"that":[26,88,143,173],"directly":[27],"reference":[28],"target":[29],"objects":[30],"properties":[32],"(\"What":[33],"is":[34,105,116,230,239],"color":[36],"car?\"),":[39],"situational":[40,97,149,180,212,250],"(such":[42],"as":[43,52],"\"Is":[44],"house":[46],"ready":[47],"for":[48,74,119,192,261],"sleeptime?\")":[49],"are":[50,145,176],"challenging":[51],"they":[53,182],"require":[54],"agent":[56],"to":[57,94,107,184,188,210,243,256,266],"correctly":[58],"identify":[59],"multiple":[60],"object-states":[61,224],"(Doors:":[62],"Closed,":[63],"Lights:":[64],"Off,":[65],"etc.)":[66],"reach":[68],"consensus":[70,101],"on":[71,129,138,269],"their":[72],"states":[73],"an":[75,91,157],"answer.":[76,205],"Towards":[77],"this":[78,139,238,278],"objective,":[79],"we":[80,141,159,194,207],"first":[81,241,255],"introduce":[82,244],"novel":[84],"Prompt-Generate-Evaluate":[85],"(PGE)":[86],"scheme":[87],"wraps":[89],"around":[90],"LLM\u2019s":[92],"output":[93],"generate":[95,108,211],"unique":[96],"corresponding":[100],"object":[102],"information.":[103],"PGE":[104,209],"used":[106],"2K":[109],"datapoints":[110],"VirtualHome":[113],"simulator,":[114],"which":[115],"then":[117],"annotated":[118],"ground":[120,168],"truth":[121,169],"answers":[122],"via":[123],"large":[125],"scale":[126],"user-study":[127],"conducted":[128],"M-Turk.":[130],"With":[131],"high":[133],"rate":[134],"answerability":[136],"(97.26%)":[137],"study,":[140],"establish":[142],"LLMs":[144,175],"good":[146,177],"at":[147,178],"generating":[148,179,222],"data.":[150],"However,":[151],"evaluating":[153],"data":[155,213],"using":[156],"LLM,":[158],"observe":[160,195],"low":[162],"correlation":[163],"46.2%":[165],"human":[170],"annotations;":[171],"indicating":[172],"while":[174],"data,":[181],"struggle":[183],"answer":[185],"them":[186],"according":[187],"consensus.":[189],"When":[190],"asked":[191],"reasoning,":[193],"LLM":[197,219],"often":[198],"goes":[199],"against":[200],"commonsense":[201],"justifying":[203],"its":[204],"Finally,":[206],"utilize":[208],"real-world":[216,272],"environment,":[217],"exposing":[218],"hallucination":[220],"reliable":[223],"when":[225],"structured":[227],"scene":[228],"graph":[229],"unavailable.":[231],"To":[232],"best":[234],"our":[236],"knowledge,":[237],"context":[248],"also":[253],"generative":[259],"approach":[260],"query":[262],"creation.":[263],"aim":[265],"foster":[267],"research":[268],"improving":[270],"usability":[273],"embodied":[275],"agents":[276],"through":[277],"work.":[279]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-28T00:00:00"}
