{"id":"https://openalex.org/W4409149367","doi":"https://doi.org/10.1145/3690624.3709250","title":"R <sup>2</sup> MR: Review and Rewrite Modality for Recommendation","display_name":"R <sup>2</sup> MR: Review and Rewrite Modality for Recommendation","publication_year":2025,"publication_date":"2025-04-04","ids":{"openalex":"https://openalex.org/W4409149367","doi":"https://doi.org/10.1145/3690624.3709250"},"language":"en","primary_location":{"id":"doi:10.1145/3690624.3709250","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690624.3709250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"},"type":"conference-paper","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/A5077755385","display_name":"Gu Tang","orcid":"https://orcid.org/0009-0008-6640-1268"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gu Tang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-6640-1268","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081560197","display_name":"Jinghe Wang","orcid":"https://orcid.org/0009-0006-2646-6660"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghe Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-2646-6660","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085791658","display_name":"Xiaoying Gan","orcid":"https://orcid.org/0000-0001-5200-1409"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoying Gan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5200-1409","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060517125","display_name":"Bin L\u00fc","orcid":"https://orcid.org/0000-0001-6452-7029"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Lu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6452-7029","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100314486","display_name":"Ze Zhao","orcid":"https://orcid.org/0000-0002-1599-3434"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ze Zhao","raw_affiliation_strings":["Shanghai Jiao Tong Universityy, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1599-3434","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong Universityy, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048486573","display_name":"Luoyi Fu","orcid":"https://orcid.org/0000-0001-7796-9168"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luoyi Fu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7796-9168","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034483183","display_name":"Xinbing Wang","orcid":"https://orcid.org/0000-0002-0357-8356"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbing Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0357-8356","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023919188","display_name":"Chenghu Zhou","orcid":"https://orcid.org/0000-0003-3331-2302"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghu Zhou","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3331-2302","affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1337","last_page":"1348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9940000176429749,"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/modality","display_name":"Modality (human\u2013computer interaction)","score":0.642000138759613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5126475691795349},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.41630202531814575},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3599068522453308},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1849905550479889}],"concepts":[{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.642000138759613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5126475691795349},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.41630202531814575},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3599068522453308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1849905550479889}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3690624.3709250","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690624.3709250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2160643434","https://openalex.org/W2741249238","https://openalex.org/W2747329762","https://openalex.org/W2752796333","https://openalex.org/W2908804015","https://openalex.org/W2912678722","https://openalex.org/W2913077324","https://openalex.org/W2962770929","https://openalex.org/W2963655167","https://openalex.org/W2982108874","https://openalex.org/W3005680577","https://openalex.org/W3024534448","https://openalex.org/W3036982689","https://openalex.org/W3045200674","https://openalex.org/W3093002391","https://openalex.org/W3094605801","https://openalex.org/W3133849783","https://openalex.org/W3153325943","https://openalex.org/W3180355996","https://openalex.org/W3192113933","https://openalex.org/W3205778609","https://openalex.org/W4205091644","https://openalex.org/W4220909642","https://openalex.org/W4224983022","https://openalex.org/W4284687944","https://openalex.org/W4285288414","https://openalex.org/W4297971002","https://openalex.org/W4304014904","https://openalex.org/W4309185982","https://openalex.org/W4312824836","https://openalex.org/W4312933868","https://openalex.org/W4317951215","https://openalex.org/W4321593910","https://openalex.org/W4322718576","https://openalex.org/W4385565673","https://openalex.org/W4385682046","https://openalex.org/W4386071957","https://openalex.org/W4387171276","https://openalex.org/W4390873054","https://openalex.org/W4393148714","https://openalex.org/W4393159797","https://openalex.org/W6677316912","https://openalex.org/W6779823529"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"With":[0],"the":[1,42,49,80,139,161],"explosive":[2],"growth":[3],"of":[4,51,82,112,148,163,191],"online":[5],"multimodal":[6,8],"content,":[7],"recommender":[9],"systems(MRSs)":[10],"have":[11],"brought":[12],"significant":[13],"benefits":[14],"to":[15,48,61,79,85,104],"multimedia":[16],"platforms.":[17],"As":[18],"MRSs":[19],"evolve,":[20],"many":[21],"studies":[22],"incorporate":[23],"advanced":[24],"technologies":[25],"like":[26],"graph":[27],"neural":[28],"networks(GNNs)":[29],"and":[30,53,99,118,137],"self-supervised":[31],"learning(SSL),":[32],"achieving":[33,187],"remarkable":[34],"results.":[35],"However,":[36],"these":[37],"efforts":[38],"still":[39],"suffer":[40],"from":[41,145,171],"quality":[43,55,141,162],"disparity":[44],"problem.":[45],"It":[46,129],"refers":[47],"mixture":[50],"high":[52],"low":[54],"across":[56,176],"items'":[57],"multiple":[58,149],"modalities,":[59],"owing":[60],"disparities":[62],"in":[63],"construction":[64],"costs":[65],"or":[66,76,87],"design":[67],"levels.":[68],"These":[69],"low-quality":[70],"modalities":[71,144,165],"often":[72],"lack":[73],"crucial":[74],"details":[75],"introduce":[77],"noise":[78],"depiction":[81],"item,":[83],"leading":[84],"insufficient":[86],"polluted":[88],"item":[89],"representation.":[90],"Therefore,":[91],"we":[92],"propose":[93],"a":[94,125,155],"novel":[95],"framework":[96],"R2MR:":[97],"Review":[98,127],"Rewrite":[100],"Modality":[101,116,119,122,152],"for":[102,143],"Recommendation":[103],"tackle":[105],"this":[106],"issue.":[107],"Specifically,":[108],"R2MR":[109,182],"is":[110],"composed":[111],"two":[113],"key":[114],"components:":[115],"Reviewer":[117,123],"Rewriter.":[120],"The":[121,151,193],"introduces":[124],"Consensus":[126],"Mechanism.":[128],"performs":[130],"perspective":[131],"decomposition":[132],"based":[133],"on":[134],"user":[135],"representations":[136],"learns":[138],"consensus":[140],"scores":[142],"diverse":[146],"perspectives":[147],"users.":[150],"Rewriter":[153],"proposes":[154],"Latent":[156],"Mapping":[157],"Model,":[158],"which":[159],"improves":[160],"inferior":[164],"by":[166],"learning":[167],"various":[168],"mapping":[169],"patterns":[170],"high-quality":[172],"modalities.":[173],"Comprehensive":[174],"experiments":[175],"three":[177],"benchmark":[178],"datasets":[179],"reveal":[180],"that":[181],"substantially":[183],"outperforms":[184],"state-of-the-art":[185],"methods,":[186],"an":[188],"average":[189],"improvement":[190],"9.20%.":[192],"implementations":[194],"are":[195],"available":[196],"at":[197],"https://github.com/gutang-97/R2MR.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}