{"id":"https://openalex.org/W7154462800","doi":"https://doi.org/10.1145/3807947","title":"A Bootstrap Pipeline for Chat-Based Image Retrieval with Effective Question Generation","display_name":"A Bootstrap Pipeline for Chat-Based Image Retrieval with Effective Question Generation","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7154462800","doi":"https://doi.org/10.1145/3807947"},"language":"en","primary_location":{"id":"doi:10.1145/3807947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807947","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3807947","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124078836","display_name":"Shikai Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156165","display_name":"Lenovo (China)","ror":"https://ror.org/04srd9d93","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikai Chen","raw_affiliation_strings":["Lenovo Group Ltd, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7821-7056","affiliations":[{"raw_affiliation_string":"Lenovo Group Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210156165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103754277","display_name":"Yicheng Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Jiang","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0008-0492-3909","affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124109386","display_name":"Jin Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156165","display_name":"Lenovo (China)","ror":"https://ror.org/04srd9d93","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Yuan","raw_affiliation_strings":["Lenovo Group Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9954-0693","affiliations":[{"raw_affiliation_string":"Lenovo Group Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210156165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008287271","display_name":"Y.S. Zhang","orcid":"https://orcid.org/0000-0002-7260-5098"},"institutions":[{"id":"https://openalex.org/I4210156165","display_name":"Lenovo (China)","ror":"https://ror.org/04srd9d93","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhang","raw_affiliation_strings":["Lenovo Group Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7260-5098","affiliations":[{"raw_affiliation_string":"Lenovo Group Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210156165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101873354","display_name":"Zhongchao Shi","orcid":"https://orcid.org/0000-0002-5216-3827"},"institutions":[{"id":"https://openalex.org/I4210156165","display_name":"Lenovo (China)","ror":"https://ror.org/04srd9d93","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongchao Shi","raw_affiliation_strings":["Lenovo Group Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5216-3827","affiliations":[{"raw_affiliation_string":"Lenovo Group Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210156165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133704420","display_name":"Jianping Fan","orcid":"https://orcid.org/0000-0003-2290-1785"},"institutions":[{"id":"https://openalex.org/I4210156165","display_name":"Lenovo (China)","ror":"https://ror.org/04srd9d93","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Fan","raw_affiliation_strings":["Lenovo Group Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2290-1785","affiliations":[{"raw_affiliation_string":"Lenovo Group Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210156165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074742406","display_name":"Xin Geng","orcid":"https://orcid.org/0000-0001-7729-0622"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Geng","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-7729-0622","affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109080063","display_name":"Yong Rui","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Rui","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9142-5914","affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41916234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"6","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.766700029373169,"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":0.766700029373169,"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":0.0471000000834465,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.04309999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7056000232696533},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.5906000137329102},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5566999912261963},{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.5117999911308289},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.499099999666214},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48669999837875366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9235000014305115},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7056000232696533},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.5906000137329102},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5566999912261963},{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.5117999911308289},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.499099999666214},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48669999837875366},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4749999940395355},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.47450000047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4726000130176544},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.46950000524520874},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4237000048160553},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.29580000042915344},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2741999924182892}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3807947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807947","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3807947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3807947","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1773149199","https://openalex.org/W1861492603","https://openalex.org/W2082453965","https://openalex.org/W2101498401","https://openalex.org/W3175176651","https://openalex.org/W3200873909","https://openalex.org/W4249013746","https://openalex.org/W4313181088","https://openalex.org/W4320507094","https://openalex.org/W4382468457","https://openalex.org/W4396821179","https://openalex.org/W4396833233","https://openalex.org/W4400526199","https://openalex.org/W4402816819","https://openalex.org/W4413145788"],"related_works":[],"abstract_inverted_index":{"Chat-based":[0],"image":[1,144],"retrieval":[2,88],"uses":[3],"Large":[4],"Language":[5],"Models":[6],"(LLM)":[7],"to":[8,12,55,68,102,132],"guide":[9],"user":[10,28],"input":[11],"enable":[13],"more":[14],"specific":[15],"and":[16,81,106,117,123,137,142,177],"precise":[17],"search":[18],"results,":[19,172],"where":[20],"LLM":[21],"can":[22,160],"enhance":[23],"this":[24,42,52,100],"process":[25],"by":[26],"asking":[27],"retrieval-oriented":[29,134],"questions":[30,67,111],"eliciting":[31],"additional":[32],"details":[33],"about":[34],"the":[35,39,56,61,65,71,83,104,109,140,143,164,180],"target":[36],"image.":[37],"Despite":[38],"potential":[40],"of":[41,63,73,86,108,120,182],"approach,":[43],"no":[44],"specialized":[45],"Questioner":[46,141],"model":[47,79,124],"has":[48],"been":[49],"developed":[50,98],"for":[51,77],"task":[53],"due":[54],"following":[57],"significant":[58],"challenges:":[59],"(a)":[60],"difficulty":[62],"determining":[64],"optimal":[66],"ask;":[69],"(b)":[70],"lack":[72],"a":[74,114,147],"suitable":[75],"protocol":[76],"fair":[78,115,148],"comparison;":[80],"(c)":[82],"notable":[84],"scarcity":[85],"dialog-to-image":[87],"data.":[89],"To":[90],"address":[91,163],"these":[92],"challenges,":[93],"two":[94],"fundamental":[95],"principles":[96],"are":[97],"in":[99],"article":[101],"ensure":[103],"simplicity":[105],"effectiveness":[107],"generated":[110],"while":[112],"enabling":[113],"comparison":[116,149],"accurate":[118],"estimation":[119],"data":[121,136,166],"quality":[122],"performance.":[125],"A":[126],"bootstrap":[127],"training":[128],"methodology":[129],"is":[130],"introduced":[131],"collect":[133],"dialog":[135],"concurrently":[138],"train":[139],"Retriever.":[145],"Under":[146],"protocol,":[150],"our":[151,157],"extensive":[152],"experiments":[153],"have":[154],"demonstrated":[155],"that":[156],"proposed":[158],"method":[159],"not":[161],"only":[162],"critical":[165],"gap":[167],"but":[168],"also":[169],"achieve":[170],"state-of-the-art":[171],"which":[173],"substantially":[174],"surpass":[175],"GPT-4o":[176],"GPT-4-Turbo":[178],"through":[179],"fine-tuning":[181],"an":[183],"8B":[184],"model.":[185]},"counts_by_year":[],"updated_date":"2026-06-09T06:18:44.609144","created_date":"2026-04-16T00:00:00"}