{"id":"https://openalex.org/W7134953885","doi":"https://doi.org/10.48550/arxiv.2603.09541","title":"Memory-Guided View Refinement for Dynamic Human-in-the-loop EQA","display_name":"Memory-Guided View Refinement for Dynamic Human-in-the-loop EQA","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7134953885","doi":"https://doi.org/10.48550/arxiv.2603.09541"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.09541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09541","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":null,"license_id":null,"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.2603.09541","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128735260","display_name":"Xin Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128775516","display_name":"Rui Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128734287","display_name":"Xun Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Xun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121491366","display_name":"Weixin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Weixin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012506409","display_name":"Chuanqing Zhuang","orcid":"https://orcid.org/0000-0002-2102-5499"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Chuanqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128771538","display_name":"Jiayuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jiayuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128798559","display_name":"Zhengda Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Zhengda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128796693","display_name":"Jun Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128754969","display_name":"Yunhong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yunhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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":0.9534000158309937,"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":0.9534000158309937,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.011300000362098217,"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":0.00570000009611249,"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/inference","display_name":"Inference","score":0.7919999957084656},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6948000192642212},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.670799970626831},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.4000000059604645},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.36629998683929443},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.3643999993801117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7950999736785889},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7919999957084656},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6948000192642212},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.670799970626831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42879998683929443},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.367900013923645},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3142000138759613},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.09541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09541","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.09541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.09541","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Embodied":[0],"Question":[1],"Answering":[2],"(EQA)":[3],"has":[4],"traditionally":[5],"been":[6],"evaluated":[7],"in":[8,20,176],"temporally":[9,104],"stable":[10,105],"environments":[11],"where":[12],"visual":[13],"evidence":[14,44,69],"can":[15],"be":[16],"accumulated":[17],"reliably.":[18],"However,":[19],"dynamic,":[21],"human-populated":[22],"scenes,":[23],"human":[24,94],"activities":[25,95],"and":[26,36,45,64,96,99,118,142,163,179],"occlusions":[27,151],"introduce":[28,81],"significant":[29],"perceptual":[30],"non-stationarity:":[31],"task-relevant":[32],"cues":[33],"are":[34],"transient":[35],"view-dependent,":[37],"while":[38,152,182],"a":[39,83,90,100,123],"store-then-retrieve":[40],"strategy":[41],"over-accumulates":[42],"redundant":[43],"increases":[46],"inference":[47,155,185],"cost.":[48],"This":[49],"setting":[50],"exposes":[51],"two":[52,88],"practical":[53],"challenges":[54],"for":[55,70],"EQA":[56,85],"agents:":[57],"resolving":[58],"ambiguity":[59],"caused":[60],"by":[61],"viewpoint-dependent":[62],"occlusions,":[63],"maintaining":[65,183],"compact":[66,157],"yet":[67],"up-to-date":[68],"efficient":[71],"inference.":[72],"To":[73,107],"enable":[74],"systematic":[75],"study":[76],"of":[77],"this":[78],"setting,":[79],"we":[80,112],"DynHiL-EQA,":[82],"human-in-the-loop":[84],"dataset":[86,167],"with":[87,103,131,156],"subsets:":[89],"Dynamic":[91],"subset":[92,102],"featuring":[93],"temporal":[97],"changes,":[98],"Static":[101],"observations.":[106],"address":[108],"the":[109,164],"above":[110],"challenges,":[111],"present":[113],"DIVRR":[114,147,170],"(Dynamic-Informed":[115],"View":[116],"Refinement":[117],"Relevance-guided":[119],"Adaptive":[120],"Memory":[121],"Selection),":[122],"training-free":[124],"framework":[125],"that":[126,169],"couples":[127],"relevance-guided":[128],"view":[129],"refinement":[130],"selective":[132],"memory":[133],"admission.":[134],"By":[135],"verifying":[136],"ambiguous":[137],"observations":[138],"before":[139],"committing":[140],"them":[141],"retaining":[143],"only":[144],"informative":[145],"evidence,":[146],"improves":[148,172],"robustness":[149],"under":[150],"preserving":[153],"fast":[154],"memory.":[158],"Extensive":[159],"experiments":[160],"on":[161],"DynHiL-EQA":[162],"established":[165],"HM-EQA":[166],"demonstrate":[168],"consistently":[171],"over":[173],"existing":[174],"baselines":[175],"both":[177],"dynamic":[178],"static":[180],"settings":[181],"high":[184],"efficiency.":[186]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-12T00:00:00"}