{"id":"https://openalex.org/W7124147225","doi":"https://doi.org/10.1109/icpads67057.2025.11322909","title":"Two Heads are Better than One: Robust Learning Meets Multi-branch Models","display_name":"Two Heads are Better than One: Robust Learning Meets Multi-branch Models","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124147225","doi":"https://doi.org/10.1109/icpads67057.2025.11322909"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11322909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11322909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"},"type":"article","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/A5123012476","display_name":"Zongyuan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zongyuan Zhang","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104255210","display_name":"Qingwen Bu","orcid":null},"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":"Qingwen Bu","raw_affiliation_strings":["Shanghai Jiao Tong University,Department of Electronic Engineering,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Department of Electronic Engineering,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122994919","display_name":"Tianyang Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tianyang Duan","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123040842","display_name":"Zheng Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zheng Lin","raw_affiliation_strings":["The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Electrical and Electronic Engineering,Hong Kong,China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072210108","display_name":"Yuhao Qing","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuhao Qing","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057230946","display_name":"Zihan Fang","orcid":"https://orcid.org/0000-0002-0844-9879"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zihan Fang","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076537836","display_name":"Heming Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Heming Cui","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science,Hong Kong,China"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050270789","display_name":"Dong Huang","orcid":"https://orcid.org/0000-0003-3923-8828"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dong Huang","raw_affiliation_strings":["School of Computing, National University of Singapore,Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore,Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5123012476"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82877156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9894999861717224,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9894999861717224,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0017000000225380063,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0010000000474974513,"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/adversarial-system","display_name":"Adversarial system","score":0.9068999886512756},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6714000105857849},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6402000188827515},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5916000008583069},{"id":"https://openalex.org/keywords/orthogonality","display_name":"Orthogonality","score":0.5461000204086304},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4708999991416931},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43950000405311584},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.41920000314712524}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9068999886512756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7542999982833862},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6714000105857849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6491000056266785},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6402000188827515},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5916000008583069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5806999802589417},{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4708999991416931},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43950000405311584},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.41920000314712524},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11322909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11322909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5045979022979736,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1914323026","display_name":null,"funder_award_id":"2022ZD0160201","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2886281300","https://openalex.org/W2963542245","https://openalex.org/W2964082701","https://openalex.org/W2964137095","https://openalex.org/W3034802054","https://openalex.org/W3199042663","https://openalex.org/W4226239489","https://openalex.org/W4300677102","https://openalex.org/W4391248691","https://openalex.org/W4400433363","https://openalex.org/W4405270020","https://openalex.org/W4408354938","https://openalex.org/W4408793875","https://openalex.org/W4409917263","https://openalex.org/W4411640202","https://openalex.org/W4413394434","https://openalex.org/W4413394553","https://openalex.org/W4416749731","https://openalex.org/W7084071276","https://openalex.org/W7117783816"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"neural":[1,38,135],"networks":[2,39],"(DNNs)":[3],"are":[4,12,180],"vulnerable":[5],"to":[6,14,18,60,69,77,107,145,182,196],"adversarial":[7,63,84,117],"examples,":[8],"in":[9],"which":[10],"DNNs":[11],"misled":[13],"false":[15],"outputs":[16],"due":[17],"inputs":[19],"containing":[20],"imperceptible":[21],"perturbations.":[22],"Adversarial":[23],"training,":[24,206],"a":[25,132,139],"reliable":[26],"and":[27,40,81,137,162,212,219,230],"effective":[28],"method":[29,186],"of":[30,37,89,124,150,170],"defense,":[31],"may":[32],"significantly":[33],"reduce":[34],"the":[35,42,54,78,83,87,113,151,223],"vulnerability":[36],"becomes":[41],"de":[43],"facto":[44],"standard":[45],"for":[46,116,205],"robust":[47,215],"learning.":[48],"While":[49],"many":[50],"recent":[51],"works":[52],"practice":[53,120],"data-centric":[55],"philosophy,":[56],"such":[57],"as":[58,93],"how":[59],"generate":[61],"better":[62],"examples":[64],"or":[65],"use":[66,202],"generative":[67],"models":[68,79,208],"produce":[70],"additional":[71,203],"training":[72],"data,":[73],"we":[74,100,130],"look":[75],"back":[76],"themselves":[80],"revisit":[82],"robustness":[85],"from":[86],"perspective":[88],"deep":[90],"feature":[91],"distribution":[92],"an":[94],"insightful":[95],"complementarity.":[96],"In":[97],"this":[98],"paper,":[99],"propose":[101,138],"Branch":[102],"Orthogonality":[103],"adveRsarial":[104],"Training":[105],"(BORT)":[106],"obtain":[108],"state-of-the-art":[109,190,224],"performance":[110],"with":[111],"solely":[112],"original":[114],"dataset":[115],"training.":[118],"To":[119],"our":[121,157,185,207],"design":[122],"idea":[123],"integrating":[125],"multiple":[126],"orthogonal":[127],"solution":[128,148],"spaces,":[129],"leverage":[131],"simple":[133],"multi-branch":[134,152],"network":[136],"corresponding":[140],"loss":[141],"function,":[142],"branch-orthogonal":[143],"loss,":[144],"make":[146],"each":[147],"space":[149],"model":[153],"orthogonal.":[154],"We":[155],"evaluate":[156],"approach":[158],"on":[159,217],"CIFAR-10,":[160],"CIFAR-100":[161,220],"SVHN":[163],"against":[164],"<tex":[165,172,226,231],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[166,173,227,232],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\ell_{\\infty}$</tex>":[167],"norm-bounded":[168],"perturbations":[169],"size":[171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\epsilon=8":[174],"/":[175],"255$</tex>,":[176],"respectively.":[177],"Exhaustive":[178],"experiments":[179],"conducted":[181],"show":[183],"that":[184,199],"goes":[187],"beyond":[188],"all":[189,197],"methods":[191,198],"without":[192],"any":[193],"tricks.":[194],"Compared":[195],"do":[200],"not":[201],"data":[204],"achieve":[209],"67.3":[210],"%":[211,214],"41.5":[213],"accuracy":[216],"CIFAR-10":[218],"(improving":[221],"upon":[222],"by":[225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{+7.23":[228],"\\%}$</tex>":[229],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{+9.07":[233],"\\%}$</tex>).":[234]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-15T00:00:00"}
