{"id":"https://openalex.org/W4396758671","doi":"https://doi.org/10.1145/3589334.3645381","title":"Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models","display_name":"Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4396758671","doi":"https://doi.org/10.1145/3589334.3645381"},"language":"en","primary_location":{"id":"doi:10.1145/3589334.3645381","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-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/A5078451082","display_name":"Hongzhan Lin","orcid":"https://orcid.org/0000-0002-4111-8334"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hongzhan Lin","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-4111-8334","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055657033","display_name":"Ziyang Luo","orcid":"https://orcid.org/0000-0002-6037-0471"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ziyang Luo","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6037-0471","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009514550","display_name":"Wei Gao","orcid":"https://orcid.org/0000-0003-2028-2407"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wei Gao","raw_affiliation_strings":["Singapore Management University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-2028-2407","affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034823980","display_name":"Jing Ma","orcid":"https://orcid.org/0000-0002-7464-8331"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jing Ma","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-7464-8331","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407999","display_name":"Bo Wang","orcid":"https://orcid.org/0000-0001-7158-7046"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0001-7158-7046","affiliations":[{"raw_affiliation_string":"Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017322880","display_name":"Ruichao Yang","orcid":"https://orcid.org/0000-0003-3749-3622"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ruichao Yang","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-3749-3622","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.0485,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.98898979,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2359","last_page":"2370"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9976999759674072,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9897000193595886,"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":0.6764736175537109},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4245983958244324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.421421617269516},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.41708970069885254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6764736175537109},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4245983958244324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.421421617269516},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.41708970069885254}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589334.3645381","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589334.3645381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2024","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2194775991","https://openalex.org/W2886641317","https://openalex.org/W2913954081","https://openalex.org/W2914304175","https://openalex.org/W2915480215","https://openalex.org/W3036394672","https://openalex.org/W3159259047","https://openalex.org/W3174604160","https://openalex.org/W3175392088","https://openalex.org/W3185341429","https://openalex.org/W3195130895","https://openalex.org/W3205961173","https://openalex.org/W3207512843","https://openalex.org/W4224320265","https://openalex.org/W4224910065","https://openalex.org/W4226278401","https://openalex.org/W4283455941","https://openalex.org/W4285606948","https://openalex.org/W4309674289","https://openalex.org/W4367047467","https://openalex.org/W4382240064","https://openalex.org/W4385573042","https://openalex.org/W4387969708","https://openalex.org/W4389520473","https://openalex.org/W4390874575","https://openalex.org/W4392669753","https://openalex.org/W6600669965"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"The":[0],"age":[1],"of":[2,17,96,211],"social":[3],"media":[4],"is":[5,35,158],"flooded":[6],"with":[7],"Internet":[8],"memes,":[9,33,77],"necessitating":[10],"a":[11,23,127,203],"clear":[12],"grasp":[13],"and":[14,43,87,104,146,166,177,201],"effective":[15],"identification":[16],"harmful":[18,47,76,88,178,190],"ones.":[19],"This":[20],"task":[21],"presents":[22],"significant":[24],"challenge":[25],"due":[26],"to":[27,61,74,113,125,138,160],"the":[28,40,93,115,119,132,143,147,208,212],"implicit":[29,59,167],"meaning":[30,60],"embedded":[31],"in":[32],"which":[34],"not":[36,52],"explicitly":[37],"conveyed":[38],"through":[39,79],"surface":[41],"text":[42,102],"image.":[44],"However,":[45],"existing":[46],"meme":[48,185,191,209],"detection":[49,64,192],"methods":[50,200],"do":[51],"present":[53],"readable":[54],"explanations":[55,116,172],"that":[56,188],"unveil":[57],"such":[58],"support":[62],"their":[63],"decisions.":[65],"In":[66,153],"this":[67,154],"paper,":[68],"we":[69,106,123],"propose":[70,124],"an":[71],"explainable":[72],"approach":[73,193],"detect":[75],"achieved":[78],"reasoning":[80,163],"over":[81,164],"conflicting":[82],"rationales":[83,145],"from":[84,118,174],"both":[85,175],"harmless":[86,176],"positions.":[89],"Specifically,":[90],"inspired":[91],"by":[92],"powerful":[94],"capacity":[95,205],"Large":[97],"Language":[98],"Models":[99],"(LLMs)":[100],"on":[101,182],"generation":[103],"reasoning,":[105],"first":[107],"elicit":[108],"multimodal":[109,140,149,171],"debate":[110,133],"between":[111,142],"LLMs":[112],"generate":[114],"derived":[117],"contradictory":[120],"arguments.":[121,179],"Then":[122],"fine-tune":[126],"small":[128],"language":[129],"model":[130,157,213],"as":[131],"judge":[134],"for":[135,206],"harmfulness":[136,144,210],"inference,":[137],"facilitate":[139],"fusion":[141],"intrinsic":[148],"information":[150],"within":[151],"memes.":[152],"way,":[155],"our":[156,189],"empowered":[159],"perform":[161],"dialectical":[162],"intricate":[165],"harm-indicative":[168],"patterns,":[169],"utilizing":[170],"originating":[173],"Extensive":[180],"experiments":[181],"three":[183],"public":[184],"datasets":[186],"demonstrate":[187],"achieves":[194],"much":[195],"better":[196],"performance":[197],"than":[198],"state-of-the-art":[199],"exhibits":[202],"superior":[204],"explaining":[207],"predictions.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-08T08:33:18.762332","created_date":"2025-10-10T00:00:00"}
