{"id":"https://openalex.org/W4412876831","doi":"https://doi.org/10.1145/3711896.3737046","title":"Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates","display_name":"Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412876831","doi":"https://doi.org/10.1145/3711896.3737046"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3737046","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737046","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737046","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737046","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090943298","display_name":"Chengqing Yu","orcid":"https://orcid.org/0000-0001-8314-8251"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengqing Yu","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455817","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0002-3282-0535"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046293929","display_name":"Chuanguang Yang","orcid":"https://orcid.org/0000-0001-5890-289X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanguang Yang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056183845","display_name":"Zezhi Shao","orcid":"https://orcid.org/0000-0002-0815-2768"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zezhi Shao","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004811602","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0003-1692-3574"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Sun","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020332722","display_name":"Tangwen Qian","orcid":"https://orcid.org/0000-0001-5694-3831"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tangwen Qian","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of ScienceS, Beijing, China and State Key Laboratory of AI Safety, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of ScienceS, Beijing, China and State Key Laboratory of AI Safety, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323842","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0003-4488-0102"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wei","raw_affiliation_strings":["School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055016576","display_name":"Zhulin An","orcid":"https://orcid.org/0000-0002-7593-8293"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhulin An","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103245119","display_name":"Yongjun Xu","orcid":"https://orcid.org/0000-0001-6647-0986"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjun Xu","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of AI Safety, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5090943298"],"corresponding_institution_ids":["https://openalex.org/I4210090176"],"apc_list":null,"apc_paid":null,"fwci":2.9744,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91739895,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3633","last_page":"3644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7974025011062622},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6059370636940002},{"id":"https://openalex.org/keywords/merlin","display_name":"Merlin (protein)","score":0.5797392129898071},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5708587169647217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5346680283546448},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5109245181083679},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.49590715765953064},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4732321500778198},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4024205803871155}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7974025011062622},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6059370636940002},{"id":"https://openalex.org/C178628643","wikidata":"https://www.wikidata.org/wiki/Q410233","display_name":"Merlin (protein)","level":4,"score":0.5797392129898071},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5708587169647217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5346680283546448},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5109245181083679},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.49590715765953064},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4732321500778198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4024205803871155},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C179185449","wikidata":"https://www.wikidata.org/wiki/Q219699","display_name":"Suppressor","level":3,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3737046","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737046","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737046","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3737046","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737046","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737046","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1905349068","display_name":null,"funder_award_id":"2023112","funder_id":"https://openalex.org/F4320322847","funder_display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences"},{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2420316557","display_name":null,"funder_award_id":"62476264","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3078953789","display_name":null,"funder_award_id":"202403","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6058138561","display_name":null,"funder_award_id":", No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6710808979","display_name":null,"funder_award_id":"62372430","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8863666567","display_name":null,"funder_award_id":"and No.","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/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"},{"id":"https://openalex.org/F4320335892","display_name":"Youth Innovation Promotion Association","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412876831.pdf","grobid_xml":"https://content.openalex.org/works/W4412876831.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W2159586267","https://openalex.org/W2965341826","https://openalex.org/W2990138404","https://openalex.org/W2997705255","https://openalex.org/W3023213286","https://openalex.org/W3035317797","https://openalex.org/W3080253043","https://openalex.org/W3092822179","https://openalex.org/W3156778566","https://openalex.org/W3159551428","https://openalex.org/W3174022889","https://openalex.org/W3174697924","https://openalex.org/W3196402958","https://openalex.org/W3197108287","https://openalex.org/W3199148273","https://openalex.org/W3199797768","https://openalex.org/W3214511793","https://openalex.org/W4205581758","https://openalex.org/W4283315029","https://openalex.org/W4283706581","https://openalex.org/W4285489795","https://openalex.org/W4306317966","https://openalex.org/W4306874801","https://openalex.org/W4308929797","https://openalex.org/W4312309807","https://openalex.org/W4312703862","https://openalex.org/W4312713717","https://openalex.org/W4313178806","https://openalex.org/W4319335604","https://openalex.org/W4319453451","https://openalex.org/W4321460300","https://openalex.org/W4327662218","https://openalex.org/W4366377753","https://openalex.org/W4379013065","https://openalex.org/W4382239356","https://openalex.org/W4386071805","https://openalex.org/W4387561305","https://openalex.org/W4387848755","https://openalex.org/W4389776308","https://openalex.org/W4392397350","https://openalex.org/W4392506574","https://openalex.org/W4393153153","https://openalex.org/W4400071817","https://openalex.org/W4400111732","https://openalex.org/W4401024000","https://openalex.org/W4401198529","https://openalex.org/W4401353384","https://openalex.org/W4401857089","https://openalex.org/W4401900250","https://openalex.org/W4403600951","https://openalex.org/W4405316565","https://openalex.org/W6601977772","https://openalex.org/W6603860191"],"related_works":["https://openalex.org/W1968661068","https://openalex.org/W2808424323","https://openalex.org/W2289963763","https://openalex.org/W433768740","https://openalex.org/W2038166529","https://openalex.org/W4210720695","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Multivariate":[0],"Time":[1],"Series":[2],"Forecasting":[3],"(MTSF)":[4],"involves":[5],"predicting":[6],"future":[7],"values":[8,45,53],"of":[9,59,116,183,188,207],"multiple":[10],"interrelated":[11],"time":[12],"series.":[13],"Recently,":[14],"deep":[15],"learning-based":[16],"MTSF":[17],"models":[18,39,70,97,190],"have":[19],"gained":[20],"significant":[21],"attention":[22],"for":[23],"their":[24,62],"promising":[25],"ability":[26],"to":[27,43,73,77,133,145],"mine":[28],"semantics":[29,58,140],"(global":[30],"and":[31,108,123],"local":[32],"information)":[33],"within":[34],"MTS":[35],"data.":[36],"However,":[37],"these":[38],"are":[40],"pervasively":[41],"susceptible":[42],"missing":[44,52,106,170,177,193],"caused":[46],"by":[47,158],"malfunctioning":[48],"data":[49,162],"collectors.":[50],"These":[51],"not":[54],"only":[55],"disrupt":[56],"the":[57,154,186,205],"MTS,":[60],"but":[61],"distribution":[63],"also":[64],"changes":[65],"over":[66],"time.":[67],"Nevertheless,":[68],"existing":[69,96,189],"lack":[71],"robustness":[72,157,187],"such":[74],"issues,":[75],"leading":[76],"suboptimal":[78],"forecasting":[79,197],"performance.":[80],"To":[81],"this":[82,85],"end,":[83],"in":[84,111,138],"paper,":[86],"we":[87],"propose":[88],"Multi-View":[89],"Representation":[90],"Learning":[91],"(Merlin),":[92],"which":[93],"can":[94],"help":[95],"achieve":[98],"semantic":[99,173],"alignment":[100,174],"between":[101],"incomplete":[102,142,166],"observations":[103,110,167],"with":[104,168],"different":[105,169,176],"rates":[107,194],"complete":[109,149],"MTS.":[112],"Specifically,":[113],"Merlin":[114,180],"consists":[115],"two":[117],"key":[118],"modules:":[119],"offline":[120],"knowledge":[121],"distillation":[122],"multi-view":[124],"contrastive":[125],"learning.":[126],"The":[127,151],"former":[128],"utilizes":[129],"a":[130,135],"teacher":[131],"model":[132,137],"guide":[134],"student":[136,155],"mining":[139],"from":[141,148,160,165],"observations,":[143],"similar":[144],"those":[146],"obtainable":[147],"observations.":[150],"latter":[152],"improves":[153],"model's":[156],"learning":[159],"positive/negative":[161],"pairs":[163],"constructed":[164],"rates,":[171],"ensuring":[172],"across":[175],"rates.":[178],"Therefore,":[179],"is":[181],"capable":[182],"effectively":[184],"enhancing":[185],"against":[191],"unfixed":[192],"while":[195],"preserving":[196],"accuracy.":[198],"Experiments":[199],"on":[200],"four":[201],"real-world":[202],"datasets":[203],"demonstrate":[204],"superiority":[206],"Merlin.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
