{"id":"https://openalex.org/W7164828656","doi":"https://doi.org/10.48550/arxiv.2606.13929","title":"Self-Evolving Visual Questioner","display_name":"Self-Evolving Visual Questioner","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164828656","doi":"https://doi.org/10.48550/arxiv.2606.13929"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13929","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13929","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.13929","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107311577","display_name":"Y Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yijun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138674389","display_name":"Hengguang Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Hengguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138673168","display_name":"Ming Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076180832","display_name":"Lichen Li","orcid":"https://orcid.org/0000-0001-6157-4946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138675814","display_name":"Cho-Jui Hsieh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsieh, Cho-Jui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138669653","display_name":"Tianyi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Tianyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.9833999872207642,"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":0.9833999872207642,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.003100000089034438,"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/diversity","display_name":"Diversity (politics)","score":0.5813999772071838},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5813000202178955},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4936000108718872},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4700999855995178},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.4408000111579895},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4374000132083893},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.36820000410079956},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3433000147342682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718000173568726},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.5813999772071838},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101000070571899},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4936000108718872},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.4408000111579895},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4032999873161316},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.36820000410079956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3637999892234802},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3149999976158142},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.31220000982284546},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3066999912261963},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2653999924659729},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C156325361","wikidata":"https://www.wikidata.org/wiki/Q1152864","display_name":"Grounded theory","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13929","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13929","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.13929","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13929","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":"Preprint"},"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":{"Vision-language":[0],"models":[1],"(VLMs)":[2],"are":[3,95],"typically":[4],"trained":[5],"as":[6,51,69],"passive":[7],"answerers,":[8],"while":[9,84],"their":[10,86],"ability":[11],"to":[12,76,89,98],"actively":[13],"ask":[14],"diverse,":[15],"non-trivial,":[16],"visual-centric":[17,82],"and":[18,73,81,105,123,139],"grounded":[19],"questions":[20,94,119],"remains":[21,169],"underexplored.":[22],"Existing":[23],"visual":[24,53],"questioners'":[25],"performance":[26],"is":[27,155],"bottlenecked":[28],"by":[29],"the":[30,37,100,110,137,142,150,161,166],"availability":[31],"of":[32,39,145],"high-quality":[33],"training":[34,91,159],"data":[35],"or":[36,172],"cost":[38],"curating":[40],"them.":[41],"We":[42,59],"show":[43,131],"that":[44,64,117,132],"a":[45,52,61,66,71,74,170],"VLM":[46,67,101],"can":[47],"continuously":[48],"improve":[49],"itself":[50,68],"questioner":[54,104,168],"without":[55],"any":[56],"external":[57],"supervision.":[58],"propose":[60],"self-evolving":[62,167],"framework":[63],"uses":[65],"both":[70,103],"proposer":[72],"filter":[75],"produce":[77],"harder,":[78],"more":[79,156],"informative,":[80],"questions,":[83],"maintaining":[85],"exploration":[87],"diversity":[88,124],"avoid":[90],"collapse.":[92],"These":[93],"then":[96],"used":[97],"train":[99],"in":[102],"answerer":[106],"modes.":[107],"To":[108],"evaluate":[109],"questioner,":[111],"we":[112],"introduce":[113],"an":[114],"agentic":[115],"protocol":[116],"assesses":[118],"along":[120],"perception,":[121],"reasoning,":[122],"dimensions.":[125],"Experiments":[126],"across":[127],"various":[128],"backbone":[129],"VLMs":[130],"our":[133,153],"method":[134],"substantially":[135,140],"enhances":[136],"quality":[138],"expands":[141],"difficulty":[143],"boundary":[144],"autonomous":[146],"question":[147],"generation.":[148],"Under":[149],"same":[151],"budget,":[152],"self-supervision":[154],"effective":[157],"than":[158],"on":[160],"static":[162],"source":[163],"data.":[164],"Moreover,":[165],"competitive":[171],"even":[173],"better":[174],"answerer.":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-16T00:00:00"}
