{"id":"https://openalex.org/W7129049910","doi":"https://doi.org/10.1145/3773966.3777948","title":"Does Homophily Help in Robust Test-time Node Classification?","display_name":"Does Homophily Help in Robust Test-time Node Classification?","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7129049910","doi":"https://doi.org/10.1145/3773966.3777948"},"language":null,"primary_location":{"id":"doi:10.1145/3773966.3777948","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777948","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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3773966.3777948","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126071065","display_name":"Yan Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yan Jiang","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005674414","display_name":"Ruihong Qiu","orcid":"https://orcid.org/0000-0001-8349-6475"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ruihong Qiu","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126137053","display_name":"Zi Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zi Huang","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5126071065"],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82628022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"271","last_page":"281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.991100013256073,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.991100013256073,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.0012000000569969416,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/homophily","display_name":"Homophily","score":0.9474999904632568},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49230000376701355},{"id":"https://openalex.org/keywords/null-model","display_name":"Null model","score":0.49219998717308044},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.47600001096725464},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.46540001034736633},{"id":"https://openalex.org/keywords/network-science","display_name":"Network science","score":0.3815000057220459},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3783999979496002},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.3686999976634979},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.33090001344680786}],"concepts":[{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.9474999904632568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6988000273704529},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C36382193","wikidata":"https://www.wikidata.org/wiki/Q7068966","display_name":"Null model","level":2,"score":0.49219998717308044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47609999775886536},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.47600001096725464},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.439300000667572},{"id":"https://openalex.org/C137753397","wikidata":"https://www.wikidata.org/wiki/Q2434424","display_name":"Network science","level":3,"score":0.3815000057220459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.3686999976634979},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.364300012588501},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C2780600066","wikidata":"https://www.wikidata.org/wiki/Q7239828","display_name":"Preferential attachment","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.30889999866485596},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C89694873","wikidata":"https://www.wikidata.org/wiki/Q4810299","display_name":"Assortativity","level":3,"score":0.27399998903274536},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C87414783","wikidata":"https://www.wikidata.org/wiki/Q1002603","display_name":"Degree distribution","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2578999996185303},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3773966.3777948","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777948","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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3773966.3777948","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777948","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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6601539850234985}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2803831897","https://openalex.org/W3166257724","https://openalex.org/W4320060387","https://openalex.org/W4391549720","https://openalex.org/W4391901119","https://openalex.org/W4391935658","https://openalex.org/W4392163152","https://openalex.org/W4392887238","https://openalex.org/W4396758742","https://openalex.org/W4400525552","https://openalex.org/W4409366133"],"related_works":[],"abstract_inverted_index":{"Homophily,":[0],"the":[1,6,100,119,138,189],"tendency":[2],"of":[3,15,142,191,204,218],"nodes":[4],"from":[5,64,77],"same":[7],"class":[8],"to":[9,178,220],"connect,":[10],"is":[11,170,176],"a":[12,158,173,202],"fundamental":[13],"property":[14],"real-world":[16,58],"graphs,":[17],"underpinning":[18],"structural":[19,162,186],"and":[20,29,68,83,112,140],"semantic":[21],"patterns":[22],"in":[23,57,80,87,105,126,132,166],"domains":[24],"such":[25,71],"as":[26,72],"citation":[27,88],"networks":[28,82],"social":[30,81],"networks.":[31],"Existing":[32],"methods":[33],"exploit":[34],"homophily":[35,125,174,193],"through":[36],"designing":[37],"homophily-aware":[38],"GNN":[39,51],"architectures":[40],"or":[41,129,152],"graph":[42,121,161,185],"structure":[43,122],"learning":[44,52],"strategies,":[45],"yet":[46],"they":[47],"primarily":[48],"focus":[49],"on":[50,145,197],"with":[53,216],"training":[54,151],"graphs.":[55],"However,":[56],"scenarios,":[59],"test":[60,120,180],"graphs":[61,90,128,134],"often":[62],"suffer":[63],"data":[65,206],"quality":[66,207],"issues":[67,208],"distribution":[69],"shifts,":[70],"domain":[73],"shifts":[74,86],"across":[75],"users":[76],"different":[78],"regions":[79],"temporal":[84],"evolution":[85],"network":[89],"collected":[91],"over":[92],"varying":[93],"time":[94],"periods.":[95],"These":[96],"factors":[97],"significantly":[98,136],"compromise":[99],"pre-trained":[101,143],"model's":[102],"robustness,":[103],"resulting":[104],"degraded":[106],"test-time":[107,160,184,205],"performance.":[108],"With":[109],"empirical":[110],"observations":[111],"theoretical":[113],"analysis,":[114],"we":[115],"reveal":[116],"that":[117,210],"transforming":[118],"by":[123,155,188],"increasing":[124],"homophilic":[127],"decreasing":[130],"it":[131],"heterophilic":[133],"can":[135],"improve":[137],"robustness":[139],"performance":[141],"GNNs":[144],"node":[146],"classifications,":[147],"without":[148],"requiring":[149],"model":[150],"update.":[153],"Motivated":[154],"these":[156],"insights,":[157],"novel":[159],"transformation":[163,187],"method":[164],"grounded":[165],"homophily,":[167],"named":[168],"GrapHoST,":[169],"proposed.":[171],"Specifically,":[172],"predictor":[175],"developed":[177],"discriminate":[179],"edges,":[181],"facilitating":[182],"adaptive":[183],"confidence":[190],"predicted":[192],"scores.":[194],"Extensive":[195],"experiments":[196],"nine":[198],"benchmark":[199],"datasets":[200],"under":[201],"range":[203],"demonstrate":[209],"GrapHoST":[211],"consistently":[212],"achieves":[213],"state-of-the-art":[214],"performance,":[215],"improvements":[217],"up":[219],"10.92%.":[221],"Our":[222],"code":[223],"has":[224],"been":[225],"released":[226],"at":[227],"https://github.com/YanJiangJerry/GrapHoST.":[228]},"counts_by_year":[],"updated_date":"2026-02-18T06:20:13.636215","created_date":"2026-02-17T00:00:00"}
