{"id":"https://openalex.org/W2965353350","doi":"https://doi.org/10.1145/3291925","title":"Show, Reward, and Tell","display_name":"Show, Reward, and Tell","publication_year":2019,"publication_date":"2019-04-30","ids":{"openalex":"https://openalex.org/W2965353350","doi":"https://doi.org/10.1145/3291925","mag":"2965353350"},"language":"en","primary_location":{"id":"doi:10.1145/3291925","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3291925","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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing City, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing City, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378733","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0001-9752-6671"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing City, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing City, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017096005","display_name":"Zechao Li","orcid":"https://orcid.org/0000-0002-5341-5985"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zechao Li","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing City, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing City, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072029041","display_name":"Jianlong Fu","orcid":"https://orcid.org/0000-0002-1025-2012"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlong Fu","raw_affiliation_strings":["Microsoft Research, Beijing City, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing City, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017597537","display_name":"Tao Mei","orcid":"https://orcid.org/0000-0003-2497-7732"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Mei","raw_affiliation_strings":["JD AI Research, Beijing City, China"],"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing City, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035112538"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.7086,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.74866225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"15","issue":"2s","first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9966999888420105,"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":0.9962999820709229,"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/closed-captioning","display_name":"Closed captioning","score":0.8398414850234985},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.8285996913909912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8216456174850464},{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.7461332082748413},{"id":"https://openalex.org/keywords/storytelling","display_name":"Storytelling","score":0.66991126537323},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5957151055335999},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5672906041145325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5127109289169312},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47415369749069214},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.468205988407135},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4541383385658264},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.41702383756637573},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.21906036138534546},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2123851180076599},{"id":"https://openalex.org/keywords/narrative","display_name":"Narrative","score":0.07103866338729858}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.8398414850234985},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.8285996913909912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8216456174850464},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.7461332082748413},{"id":"https://openalex.org/C2776538412","wikidata":"https://www.wikidata.org/wiki/Q989963","display_name":"Storytelling","level":3,"score":0.66991126537323},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5957151055335999},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5672906041145325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5127109289169312},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47415369749069214},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.468205988407135},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4541383385658264},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.41702383756637573},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.21906036138534546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2123851180076599},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.07103866338729858},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3291925","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3291925","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":null,"license_id":null,"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":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W648786980","https://openalex.org/W1586939924","https://openalex.org/W1895577753","https://openalex.org/W1947481528","https://openalex.org/W1956340063","https://openalex.org/W2042708146","https://openalex.org/W2066134726","https://openalex.org/W2101105183","https://openalex.org/W2112912048","https://openalex.org/W2119717200","https://openalex.org/W2125308790","https://openalex.org/W2125389028","https://openalex.org/W2139501017","https://openalex.org/W2302086703","https://openalex.org/W2519936666","https://openalex.org/W2549599535","https://openalex.org/W2550553598","https://openalex.org/W2552161745","https://openalex.org/W2552639984","https://openalex.org/W2607119937","https://openalex.org/W2620666060","https://openalex.org/W2750779823","https://openalex.org/W2832876791","https://openalex.org/W2949376505","https://openalex.org/W2962968835","https://openalex.org/W2963084599","https://openalex.org/W2963248296","https://openalex.org/W2963576560","https://openalex.org/W2963758027","https://openalex.org/W3000226596","https://openalex.org/W3103022576","https://openalex.org/W4236965008","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W2984518291","https://openalex.org/W2973208549","https://openalex.org/W3089780482","https://openalex.org/W2523469089","https://openalex.org/W2964268978","https://openalex.org/W3100650951","https://openalex.org/W4288804510","https://openalex.org/W2965353350","https://openalex.org/W2998257508","https://openalex.org/W4287728236"],"abstract_inverted_index":{"Despite":[0],"the":[1,23,65,70,96,101,121,130,134,150,159,164,170,173],"promising":[2],"progress":[3],"made":[4],"in":[5,25,32],"visual":[6,10],"captioning":[7],"and":[8,31,58,69,89,133,156],"paragraphing,":[9],"storytelling":[11],"is":[12,18],"still":[13],"largely":[14],"unexplored.":[15],"This":[16],"task":[17],"more":[19,87],"challenging":[20],"due":[21],"to":[22,63,85,98,106,119,142,146],"difficulty":[24],"modeling":[26],"an":[27,50,76],"ordered":[28,66],"photo":[29,67],"sequence":[30,68],"generating":[33],"a":[34,112],"relevant":[35,90],"paragraph":[36,103],"with":[37,45,55],"expressive":[38],"language":[39],"style":[40],"for":[41],"storytelling.":[42],"To":[43],"deal":[44],"these":[46],"challenges,":[47],"we":[48,74,110,127],"propose":[49,75],"Attribute-based":[51],"Hierarchical":[52],"Generative":[53],"model":[54,64],"Reinforcement":[56],"Learning":[57],"adversarial":[59],"training":[60],"(AHGRL).":[61],"First,":[62],"complex":[71,102],"story":[72,131],"structure,":[73],"attribute-based":[77],"hierarchical":[78,93],"generator.":[79,160],"The":[80,92,139],"generator":[81,97,122,132,140],"incorporates":[82],"semantic":[83],"attributes":[84],"create":[86,143],"accurate":[88],"descriptions.":[91],"framework":[94],"enables":[95],"learn":[99],"from":[100],"structure.":[104],"Second,":[105],"generate":[107],"story-style":[108],"paragraphs,":[109],"design":[111],"language-style":[113],"discriminator,":[114],"which":[115],"provides":[116],"word-level":[117],"rewards":[118],"optimize":[120],"by":[123],"policy":[124],"gradient.":[125],"Third,":[126],"further":[128,157],"consider":[129],"reward":[135],"critic":[136,151],"as":[137],"adversaries.":[138],"aims":[141,152],"indistinguishable":[144],"paragraphs":[145],"human-level":[147],"stories,":[148],"whereas":[149],"at":[153],"distinguishing":[154],"them":[155],"improving":[158],"Extensive":[161],"experiments":[162],"on":[163],"widely":[165],"used":[166],"dataset":[167],"well":[168],"demonstrate":[169],"advantages":[171],"of":[172],"proposed":[174],"method":[175],"over":[176],"state-of-the-art":[177],"methods.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-08-13T00:00:00"}