iBet uBet
web content aggregator. Adding the entire web to your favor.
Link to original content:
https://api.openalex.org/works/doi:10.48550/ARXIV.2408.03202
{"id":"https://openalex.org/W4403622867","doi":"https://doi.org/10.48550/arxiv.2408.03202","title":"A Debiased Nearest Neighbors Framework for Multi-Label Text\n Classification","display_name":"A Debiased Nearest Neighbors Framework for Multi-Label Text\n Classification","publication_year":2024,"publication_date":"2024-08-06","ids":{"openalex":"https://openalex.org/W4403622867","doi":"https://doi.org/10.48550/arxiv.2408.03202"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.03202","pdf_url":"http://arxiv.org/pdf/2408.03202","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2408.03202","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033620369","display_name":"Zifeng Cheng","orcid":"https://orcid.org/0000-0002-8486-2614"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Zifeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050282787","display_name":"Zhiwei Jiang","orcid":"https://orcid.org/0000-0001-8203-6151"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhiwei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086045813","display_name":"Yafeng Yin","orcid":"https://orcid.org/0000-0003-3117-5463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Yafeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013289027","display_name":"Zhaoling Chen","orcid":"https://orcid.org/0009-0000-0041-5255"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhaoling","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390438","display_name":"Cong Wang","orcid":"https://orcid.org/0000-0001-7831-3486"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Cong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044227484","display_name":"Shiping Ge","orcid":"https://orcid.org/0000-0001-9198-5324"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Shiping","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046615638","display_name":"Qiguo Huang","orcid":"https://orcid.org/0000-0001-7912-7175"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Qiguo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110659766","display_name":"Qing Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Qing","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":85},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Multi-label Text Classification in Machine Learning","score":0.9697,"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":"Multi-label Text Classification in Machine Learning","score":0.9697,"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/multi-label-learning","display_name":"Multi-label Learning","score":0.710053},{"id":"https://openalex.org/keywords/text-classification","display_name":"Text Classification","score":0.597376},{"id":"https://openalex.org/keywords/hierarchical-classification","display_name":"Hierarchical Classification","score":0.544419},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature Selection","score":0.544121},{"id":"https://openalex.org/keywords/document-categorization","display_name":"Document Categorization","score":0.540188}],"concepts":[{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6562376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6306998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.51435935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44750085}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.03202","pdf_url":"http://arxiv.org/pdf/2408.03202","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.03202","pdf_url":"http://arxiv.org/pdf/2408.03202","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391913857","https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2166213322","https://openalex.org/W2147397890","https://openalex.org/W2062957446","https://openalex.org/W2042327336","https://openalex.org/W2033914206"],"abstract_inverted_index":{"Multi-Label":[0],"Text":[1],"Classification":[2],"(MLTC)":[3],"is":[4],"a":[5,93,114,131],"practical":[6],"yet":[7],"challenging":[8],"task":[9],"that":[10],"involves":[11],"assigning":[12],"multiple":[13],"non-exclusive":[14],"labels":[15],"to":[16,27,60,103],"each":[17],"document.":[18],"Previous":[19],"studies":[20],"primarily":[21],"focus":[22],"on":[23,122,151],"capturing":[24],"label":[25,29,62,123],"correlations":[26],"assist":[28],"prediction":[30,86],"by":[31,54],"introducing":[32],"special":[33],"labeling":[34],"schemes,":[35],"designing":[36],"specific":[37],"model":[38],"structures,":[39],"or":[40],"adding":[41],"auxiliary":[42],"tasks.":[43],"Recently,":[44],"the":[45,66,137,163],"$k$":[46],"Nearest":[47,95],"Neighbor":[48],"($k$NN)":[49],"framework":[50,98],"has":[51],"shown":[52],"promise":[53],"retrieving":[55],"labeled":[56],"samples":[57],"as":[58],"references":[59],"mine":[61],"co-occurrence":[63],"information":[64],"in":[65],"embedding":[67,74,109],"space.":[68],"However,":[69],"two":[70],"critical":[71],"biases,":[72],"namely":[73],"alignment":[75,110],"bias":[76],"and":[77,144,160],"confidence":[78,126,133],"estimation":[79,127,134],"bias,":[80,111,128],"are":[81],"often":[82],"overlooked,":[83],"adversely":[84],"affecting":[85],"performance.":[87],"In":[88],"this":[89],"paper,":[90],"we":[91,112,129],"introduce":[92,174],"DEbiased":[94],"Neighbors":[96],"(DENN)":[97],"for":[99],"MLTC,":[100],"specifically":[101],"designed":[102],"mitigate":[104],"these":[105],"biases.":[106],"To":[107],"address":[108],"propose":[113],"debiased":[115,132],"contrastive":[116],"learning":[117],"strategy,":[118,135],"enhancing":[119],"neighbor":[120],"consistency":[121],"co-occurrence.":[124],"For":[125],"present":[130],"improving":[136],"adaptive":[138],"combination":[139],"of":[140,165],"predictions":[141],"from":[142],"$k$NN":[143],"inductive":[145],"binary":[146],"classifications.":[147],"Extensive":[148],"experiments":[149],"conducted":[150],"four":[152],"public":[153],"benchmark":[154],"datasets":[155],"(i.e.,":[156],"AAPD,":[157],"RCV1-V2,":[158],"Amazon-531,":[159],"EUR-LEX57K)":[161],"showcase":[162],"effectiveness":[164],"our":[166,170],"proposed":[167],"method.":[168],"Besides,":[169],"method":[171],"does":[172],"not":[173],"any":[175],"extra":[176],"parameters.":[177]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4403622867","counts_by_year":[],"updated_date":"2024-11-23T01:42:27.729124","created_date":"2024-10-22"}
