{"id":"https://openalex.org/W4414536465","doi":"https://doi.org/10.1145/3746252.3761241","title":"Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification","display_name":"Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification","publication_year":2025,"publication_date":"2025-11-07","ids":{"openalex":"https://openalex.org/W4414536465","doi":"https://doi.org/10.1145/3746252.3761241"},"language":"en","primary_location":{"id":"doi:10.1145/3746252.3761241","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.13452","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024991316","display_name":"Ruobing Jiang","orcid":"https://orcid.org/0000-0003-1209-078X"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruobing Jiang","raw_affiliation_strings":["Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-1209-078X","affiliations":[{"raw_affiliation_string":"Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mengzhe Liu","orcid":"https://orcid.org/0009-0002-7525-397X"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzhe Liu","raw_affiliation_strings":["Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0009-0002-7525-397X","affiliations":[{"raw_affiliation_string":"Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041155283","display_name":"Haobing Liu","orcid":"https://orcid.org/0000-0002-2546-3306"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haobing Liu","raw_affiliation_strings":["Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-2546-3306","affiliations":[{"raw_affiliation_string":"Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021981732","display_name":"Yanwei Yu","orcid":"https://orcid.org/0000-0002-5924-1410"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwei Yu","raw_affiliation_strings":["Ocean University of China, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-5924-1410","affiliations":[{"raw_affiliation_string":"Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59028903"],"apc_list":null,"apc_paid":null,"fwci":2.7971,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91428281,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1190","last_page":"1199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9794999957084656,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9794999957084656,"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/classifier","display_name":"Classifier (UML)","score":0.7117999792098999},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6561999917030334},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.37630000710487366},{"id":"https://openalex.org/keywords/random-noise","display_name":"Random noise","score":0.37209999561309814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3416000008583069}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7117999792098999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705299973487854},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6561999917030334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6100999712944031},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5789999961853027},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3822999894618988},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.37630000710487366},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746252.3761241","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.13452","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.13452","pdf_url":"https://arxiv.org/pdf/2508.13452","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.13452","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.13452","pdf_url":"https://arxiv.org/pdf/2508.13452","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1603781705","display_name":null,"funder_award_id":"62302469","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3613340060","display_name":null,"funder_award_id":"62176243","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3664247806","display_name":null,"funder_award_id":"ZR2022QF050","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414536465.pdf","grobid_xml":"https://content.openalex.org/works/W4414536465.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Hierarchical":[0,127],"Multi-Label":[1],"Classification":[2],"(HMC)":[3],"faces":[4],"critical":[5],"challenges":[6],"in":[7,15,96],"maintaining":[8],"structural":[9],"consistency":[10,52,135],"and":[11,39,60,136,149],"balancing":[12],"loss":[13],"weighting":[14],"Multi-Task":[16],"Learning":[17],"(MTL).":[18],"In":[19],"order":[20],"to":[21,66,116,132],"address":[22],"these":[23],"issues,":[24],"we":[25,121],"propose":[26],"a":[27,104,123],"classifier":[28,49,157],"called":[29,126],"HCAL":[30],"based":[31],"on":[32],"MTL":[33,98],"integrated":[34],"with":[35,56],"prototype":[36,55,105,115],"contrastive":[37],"learning":[38],"adaptive":[40,75],"task-weighting":[41],"mechanisms.":[42],"The":[43,69],"most":[44],"significant":[45],"advantage":[46,72],"of":[47,154],"our":[48],"is":[50,73,108],"semantic":[51],"including":[53],"both":[54,144],"explicitly":[57],"modeling":[58],"label":[59],"feature":[61],"aggregation":[62],"from":[63],"child":[64],"classes":[65],"parent":[67],"classes.":[68],"other":[70],"important":[71],"an":[74],"loss-weighting":[76],"mechanism":[77,107],"that":[78],"dynamically":[79],"allocates":[80],"optimization":[81,93],"resources":[82],"by":[83,110],"monitoring":[84],"task-specific":[85],"convergence":[86],"rates.":[87],"It":[88],"effectively":[89],"resolves":[90],"the":[91,145,155],"''one-strong-many-weak''":[92],"bias":[94],"inherent":[95],"traditional":[97],"approaches.":[99],"To":[100],"further":[101],"enhance":[102],"robustness,":[103],"perturbation":[106],"formulated":[109],"injecting":[111],"controlled":[112],"noise":[113],"into":[114],"expand":[117],"decision":[118],"boundaries.":[119],"Additionally,":[120],"formalize":[122],"quantitative":[124],"metric":[125],"Violation":[128],"Rate":[129],"(HVR)":[130],"as":[131],"evaluate":[133],"hierarchical":[134,151],"generalization.":[137],"Extensive":[138],"experiments":[139],"across":[140],"three":[141],"datasets":[142],"demonstrate":[143],"higher":[146],"classification":[147],"accuracy":[148],"reduced":[150],"violation":[152],"rate":[153],"proposed":[156],"over":[158],"baseline":[159],"models.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}