{"id":"https://openalex.org/W4415540117","doi":"https://doi.org/10.1145/3746027.3755127","title":"DARL: Mitigating Gradient Conflicts in Long-Tailed Out-of-Distribution Learning","display_name":"DARL: Mitigating Gradient Conflicts in Long-Tailed Out-of-Distribution Learning","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540117","doi":"https://doi.org/10.1145/3746027.3755127"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3755127","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755127","pdf_url":null,"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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3755127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuan Zhang","orcid":"https://orcid.org/0009-0003-0144-2628"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Zhang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-0144-2628","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038405976","display_name":"Sin Chee Chin","orcid":"https://orcid.org/0000-0002-3643-3022"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sinchee Chin","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3643-3022","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079361172","display_name":"Jing\u2010Hao Xue","orcid":"https://orcid.org/0000-0003-1174-610X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing-Hao Xue","raw_affiliation_strings":["Department of Statistical Science, University College London, London, England, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-1174-610X","affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College London, London, England, United Kingdom","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038412984","display_name":"Xiaochen Yang","orcid":"https://orcid.org/0000-0002-9299-5951"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiaochen Yang","raw_affiliation_strings":["School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-9299-5951","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026184280","display_name":"Wenming Yang","orcid":"https://orcid.org/0000-0002-2506-1286"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Yang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2506-1286","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6868","last_page":"6877"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9933000206947327,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9912999868392944,"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/ambiguity","display_name":"Ambiguity","score":0.6729000210762024},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5565000176429749},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4399999976158142},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.4146000146865845},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3555000126361847},{"id":"https://openalex.org/keywords/proposition","display_name":"Proposition","score":0.3111000061035156}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6729000210762024},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593000292778015},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5565000176429749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48350000381469727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4560000002384186},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.4146000146865845},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31139999628067017},{"id":"https://openalex.org/C2777152325","wikidata":"https://www.wikidata.org/wiki/Q108163","display_name":"Proposition","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3755127","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755127","pdf_url":null,"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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.gla.ac.uk:362813","is_oa":true,"landing_page_url":"https://eprints.gla.ac.uk/view/author/57667.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceedings"}],"best_oa_location":{"id":"doi:10.1145/3746027.3755127","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755127","pdf_url":null,"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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2732026016","https://openalex.org/W3014524176","https://openalex.org/W4380487448","https://openalex.org/W4385212332","https://openalex.org/W4387842467","https://openalex.org/W4399923983"],"related_works":[],"abstract_inverted_index":{"Long-tailed":[0],"out-of-distribution":[1,15],"learning":[2,90],"aims":[3],"to":[4,124],"reduce":[5,188],"performance":[6,168],"bias":[7,154],"in":[8,48,109,198],"long-tailed":[9,40,88,170],"in-distribution":[10],"(ID)":[11],"data":[12,104,190],"while":[13,155],"rejecting":[14],"(OOD)":[16],"samples,":[17],"which":[18,186],"are":[19],"often":[20],"mistaken":[21],"for":[22,63,83,129],"under-represented":[23],"tail":[24,64],"classes.":[25],"To":[26,73],"achieve":[27],"OOD":[28,89,131,171],"detection,":[29],"existing":[30],"methods":[31],"incorporate":[32],"an":[33,86,136],"outlier":[34],"exposure":[35],"(OE)":[36],"term":[37,53],"into":[38],"the":[39,51,59,68,75,101,107,118,144,165,176,183,189],"recognition":[41],"(LTR)":[42],"loss.":[43],"However,":[44],"as":[45,126],"we":[46,78,98,134],"prove":[47],"this":[49],"paper,":[50],"OE":[52,110,177],"induces":[54],"a":[55,127],"gradient":[56],"conflict":[57,108],"with":[58,175],"ID":[60,103,120,184],"objectives,":[61],"especially":[62],"classes,":[65],"thereby":[66],"contradicting":[67],"core":[69],"motivation":[70],"of":[71,169],"LTR.":[72],"avoid":[74],"ID-OOD":[76],"dilemma,":[77],"propose":[79],"Dynamic":[80],"Ambiguity-aware":[81],"Recalibration":[82],"Logits":[84],"(DARL),":[85],"ambiguity-guided":[87],"approach,":[91],"grounded":[92],"on":[93,182],"two":[94],"theoretical":[95],"insights.":[96],"First,":[97],"show":[99,161],"that":[100,140,162],"mixed":[102],"can":[105,141,187],"mitigate":[106],"training":[111],"and":[112],"exhibits":[113],"higher":[114],"intrinsic":[115],"ambiguity":[116,149],"than":[117],"original":[119],"data,":[121,185],"thus":[122],"able":[123],"serve":[125],"surrogate":[128],"real":[130],"data.":[132],"Second,":[133],"introduce":[135],"ambiguity-aware":[137],"logit":[138],"adjustment":[139],"dynamically":[142],"calibrate":[143],"class":[145],"margins":[146],"using":[147],"energy-based":[148],"metrics,":[150],"effectively":[151],"reducing":[152],"early-stage":[153],"avoiding":[156],"late-stage":[157],"overfitting.":[158],"Extensive":[159],"experiments":[160],"DARL":[163,179],"achieves":[164],"overall":[166],"state-of-the-art":[167],"learning.":[172],"Moreover,":[173],"compared":[174],"methods,":[178],"trains":[180],"solely":[181],"requirements":[191],"by":[192],"80%.":[193],"The":[194],"code":[195],"is":[196],"available":[197],"https://github.com/XuanZhang-A/DARL.":[199]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}