{"id":"https://openalex.org/W4364322162","doi":"https://doi.org/10.1109/tmm.2023.3265816","title":"A Dual Reinforcement Learning Framework for Weakly Supervised Phrase Grounding","display_name":"A Dual Reinforcement Learning Framework for Weakly Supervised Phrase Grounding","publication_year":2023,"publication_date":"2023-04-10","ids":{"openalex":"https://openalex.org/W4364322162","doi":"https://doi.org/10.1109/tmm.2023.3265816"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3265816","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2023.3265816","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5100357180","display_name":"Zhiyu Wang","orcid":"https://orcid.org/0000-0002-0041-2924"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyu Wang","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604018","display_name":"Chao Yang","orcid":"https://orcid.org/0000-0001-8774-8115"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Yang","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007360513","display_name":"Bin Jiang","orcid":"https://orcid.org/0000-0002-5840-9664"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Jiang","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085245110","display_name":"Junsong Yuan","orcid":"https://orcid.org/0000-0002-7901-8793"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junsong Yuan","raw_affiliation_strings":["Department of Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100357180"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.369,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57556036,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"26","issue":null,"first_page":"394","last_page":"405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.8311904668807983},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.8010126352310181},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7550157308578491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6806713342666626},{"id":"https://openalex.org/keywords/noun-phrase","display_name":"Noun phrase","score":0.552123486995697},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.4770875871181488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43776318430900574},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4181712865829468},{"id":"https://openalex.org/keywords/ground","display_name":"Ground","score":0.41658711433410645},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41614586114883423},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12677758932113647},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.12048202753067017}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8311904668807983},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.8010126352310181},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7550157308578491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6806713342666626},{"id":"https://openalex.org/C153962237","wikidata":"https://www.wikidata.org/wiki/Q1401131","display_name":"Noun phrase","level":3,"score":0.552123486995697},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.4770875871181488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43776318430900574},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4181712865829468},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.41658711433410645},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41614586114883423},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12677758932113647},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.12048202753067017},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3265816","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tmm.2023.3265816","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3773955618","display_name":null,"funder_award_id":"2021JJ30152","funder_id":"https://openalex.org/F4320322866","funder_display_name":"Natural Science Foundation of Hainan Province"},{"id":"https://openalex.org/G6510101181","display_name":null,"funder_award_id":"62072169","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6668546377","display_name":null,"funder_award_id":"62172156","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322866","display_name":"Natural Science Foundation of Hainan Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1773149199","https://openalex.org/W1861492603","https://openalex.org/W1895577753","https://openalex.org/W1905882502","https://openalex.org/W1933349210","https://openalex.org/W2037227137","https://openalex.org/W2101105183","https://openalex.org/W2143612262","https://openalex.org/W2145339207","https://openalex.org/W2162349892","https://openalex.org/W2247513039","https://openalex.org/W2250539671","https://openalex.org/W2251512949","https://openalex.org/W2257979135","https://openalex.org/W2277195237","https://openalex.org/W2489434015","https://openalex.org/W2558535589","https://openalex.org/W2571175805","https://openalex.org/W2583360688","https://openalex.org/W2606473278","https://openalex.org/W2732026016","https://openalex.org/W2745461083","https://openalex.org/W2767577934","https://openalex.org/W2798990097","https://openalex.org/W2892245540","https://openalex.org/W2898071615","https://openalex.org/W2962793481","https://openalex.org/W2963080533","https://openalex.org/W2963084599","https://openalex.org/W2963109634","https://openalex.org/W2963445828","https://openalex.org/W2963758027","https://openalex.org/W2963914122","https://openalex.org/W2963976294","https://openalex.org/W2964137095","https://openalex.org/W2965033324","https://openalex.org/W2966466719","https://openalex.org/W2981951787","https://openalex.org/W2983358816","https://openalex.org/W2984194315","https://openalex.org/W2987734933","https://openalex.org/W2989176720","https://openalex.org/W3035552787","https://openalex.org/W3083600713","https://openalex.org/W3098232790","https://openalex.org/W3100393531","https://openalex.org/W3110435696","https://openalex.org/W3112077297","https://openalex.org/W3117585461","https://openalex.org/W3178418424","https://openalex.org/W3179041377","https://openalex.org/W3186567887","https://openalex.org/W4205421564","https://openalex.org/W4210820868","https://openalex.org/W4214490042","https://openalex.org/W4214650614","https://openalex.org/W4225517085","https://openalex.org/W4249013746","https://openalex.org/W4283688199","https://openalex.org/W4296339243","https://openalex.org/W4309181071","https://openalex.org/W4312351586","https://openalex.org/W4312845548","https://openalex.org/W4313145013","https://openalex.org/W4313162371","https://openalex.org/W6620707391","https://openalex.org/W6630875275","https://openalex.org/W6683204974","https://openalex.org/W6719057275","https://openalex.org/W6729383884","https://openalex.org/W6767047860","https://openalex.org/W6791353385"],"related_works":["https://openalex.org/W2039546652","https://openalex.org/W2021787609","https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W4380318855","https://openalex.org/W1537063595","https://openalex.org/W4234899305","https://openalex.org/W2012262991","https://openalex.org/W2054767487","https://openalex.org/W2785712252"],"abstract_inverted_index":{"Weakly-supervised":[0],"phrase":[1,44,108,117,120,212],"grounding":[2,80,109,118,162,213],"aims":[3],"to":[4,14,49,104,136,159,170,184,197,202],"localize":[5],"a":[6,67,98,127,194,231],"specific":[7],"region":[8],"in":[9,31,60,70,85,93],"an":[10,39],"image":[11,26],"that":[12,130,223],"corresponds":[13],"the":[15,20,32,55,61,74,78,89,107,114,138,149,152,161,172,177,186,220,227],"given":[16],"textual":[17],"phrase,":[18],"where":[19],"mapping":[21],"between":[22,73],"noun":[23],"phrases":[24],"and":[25,77,119,155,175,216,219],"regions":[27,154],"is":[28],"not":[29],"available":[30],"training":[33,187],"stage.":[34],"Previous":[35],"methods":[36,229],"typically":[37],"exploit":[38],"additional":[40],"proxy":[41,75],"task":[42],"(e.g.,":[43],"reconstruction":[45],"or":[46],"image-phrase":[47],"alignment)":[48],"provide":[50,132],"supervision":[51],"for":[52,88],"training,":[53],"since":[54],"lack":[56],"of":[57,116,140,151,189],"region-level":[58],"annotations":[59],"weakly-supervised":[62],"setting.":[63],"However,":[64],"there":[65],"exists":[66],"significant":[68],"gap":[69],"optimization":[71,87],"objectives":[72],"tasks":[76,125],"target":[79,90],"task,":[81],"which":[82],"may":[83],"result":[84],"low-efficient":[86],"model.":[91,110],"Therefore,":[92],"this":[94,144],"paper,":[95],"we":[96,112,146,192],"propose":[97],"novel":[99],"dual":[100],"reinforcement":[101,180],"learning":[102],"framework":[103],"directly":[105],"optimize":[106,160],"Specifically,":[111],"consider":[113],"duality":[115],"generation":[121],"tasks.":[122],"These":[123],"two":[124,167,210],"form":[126],"closed":[128],"loop":[129],"can":[131,147],"quality":[133],"feedback":[134,173],"signals":[135,174],"measure":[137,148],"performance":[139],"each":[141],"other.":[142],"In":[143,182],"way,":[145],"correctness":[150],"localized":[153],"thus":[156],"be":[157],"able":[158],"model":[163],"directly.":[164],"We":[165,206],"design":[166],"reward":[168],"functions":[169],"quantify":[171],"train":[176],"models":[178],"via":[179],"learning.":[181],"addition,":[183],"relieve":[185],"difficulty":[188],"our":[190,204,224],"framework,":[191],"present":[193],"heuristic":[195],"algorithm":[196],"generate":[198],"pseudo":[199],"region-phrase":[200],"pairs":[201],"warm-start":[203],"models.":[205],"perform":[207],"experiments":[208],"on":[209],"popular":[211],"datasets:":[214],"ReferItGame":[215],"Flickr30K":[217],"Entities,":[218],"results":[221],"demonstrate":[222],"method":[225],"outperforms":[226],"previous":[228],"by":[230],"large":[232],"margin.":[233]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}