{"id":"https://openalex.org/W4412825872","doi":"https://doi.org/10.1145/3711896.3736945","title":"EVI <i>N</i> ET: Towards Open-World Graph Learning via Evidential Reasoning Network","display_name":"EVI <i>N</i> ET: Towards Open-World Graph Learning via Evidential Reasoning Network","publication_year":2025,"publication_date":"2025-08-01","ids":{"openalex":"https://openalex.org/W4412825872","doi":"https://doi.org/10.1145/3711896.3736945"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3736945","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736945","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 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3711896.3736945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070435404","display_name":"Weijie Guan","orcid":"https://orcid.org/0000-0003-4001-7862"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Weijie Guan","raw_affiliation_strings":["Virginia Polytechnic Institute and State University, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4001-7862","affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012896342","display_name":"Haohui Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haohui Wang","raw_affiliation_strings":["Virginia Polytechnic Institute and State University, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0009-0000-7391-096X","affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700905","display_name":"Jian Kang","orcid":"https://orcid.org/0000-0003-3902-7131"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Kang","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-3902-7131","affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016462374","display_name":"Lihui Liu","orcid":"https://orcid.org/0000-0002-3758-4041"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lihui Liu","raw_affiliation_strings":["Wayne State University, Detroit, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-3758-4041","affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022696348","display_name":"Dawei Zhou","orcid":"https://orcid.org/0000-0002-7065-2990"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawei Zhou","raw_affiliation_strings":["Virginia Polytechnic Institute and State University, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7065-2990","affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070435404"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08826689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"709","last_page":"720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9976000189781189,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9933000206947327,"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/computer-science","display_name":"Computer science","score":0.6037803292274475},{"id":"https://openalex.org/keywords/evidential-reasoning-approach","display_name":"Evidential reasoning approach","score":0.5580108761787415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4638388752937317},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4281400144100189},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2030712068080902},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.15662997961044312}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6037803292274475},{"id":"https://openalex.org/C156201811","wikidata":"https://www.wikidata.org/wiki/Q5418360","display_name":"Evidential reasoning approach","level":4,"score":0.5580108761787415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4638388752937317},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4281400144100189},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2030712068080902},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.15662997961044312},{"id":"https://openalex.org/C97944126","wikidata":"https://www.wikidata.org/wiki/Q5001864","display_name":"Business decision mapping","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3711896.3736945","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736945","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 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/137728","is_oa":true,"landing_page_url":"https://hdl.handle.net/10919/137728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:arXiv.org:2506.07288","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.07288","pdf_url":"https://arxiv.org/pdf/2506.07288","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doi:10.1145/3711896.3736945","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736945","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 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1237271320","display_name":null,"funder_award_id":"HR00112490370, HR001124S0013","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G3107702064","display_name":null,"funder_award_id":"IIS-2339989, 2406439","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G7372066588","display_name":null,"funder_award_id":"17STCIN00001-08-00","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2230508580","https://openalex.org/W2560674852","https://openalex.org/W2747329762","https://openalex.org/W2892237532","https://openalex.org/W2962756421","https://openalex.org/W2963968551","https://openalex.org/W3014073986","https://openalex.org/W3048861846","https://openalex.org/W3097300053","https://openalex.org/W3205135396","https://openalex.org/W3215602957","https://openalex.org/W4206593497","https://openalex.org/W4285143611","https://openalex.org/W4309102176","https://openalex.org/W4381744990","https://openalex.org/W4382598033","https://openalex.org/W4386075807","https://openalex.org/W4401863605","https://openalex.org/W6600238479","https://openalex.org/W6712758098"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Graph":[0],"learning":[1,31],"has":[2],"been":[3],"crucial":[4],"to":[5,41,53],"many":[6],"real-world":[7],"tasks,":[8],"but":[9],"they":[10],"are":[11,164],"often":[12],"studied":[13],"with":[14,18],"a":[15,25,50,57,82,94],"closed-world":[16],"assumption,":[17],"all":[19],"possible":[20],"labels":[21],"of":[22,56,128,140],"data":[23,55,163],"known":[24,58],"priori.":[26],"To":[27],"enable":[28],"effective":[29],"graph":[30,158],"in":[32,125],"an":[33],"open":[34],"and":[35,108,133,143,149,152,162],"noisy":[36],"environment,":[37],"it":[38],"is":[39],"critical":[40],"inform":[42],"the":[43,47,65,126,138,154],"model":[44,48,66],"users":[45],"when":[46,64],"makes":[49],"wrong":[51],"prediction":[52],"in-distribution":[54,129],"class,":[59],"i.e.,":[60,72],"misclassification":[61,106,131,147],"detection":[62,107,148,151],"or":[63],"encounters":[67],"out-of-distribution":[68,73,112,134,150],"from":[69],"novel":[70],"classes,":[71],"detection.":[74,113,135],"This":[75],"paper":[76],"introduces":[77],"Evidential":[78],"Reasoning":[79,104,110],"Network":[80],"(EVINET),":[81],"framework":[83],"that":[84,117],"addresses":[85],"these":[86],"two":[87,100],"challenges":[88],"by":[89],"integrating":[90],"Beta":[91],"embedding":[92],"within":[93],"subjective":[95],"logic":[96],"framework.":[97],"EVINET":[98,118,136],"includes":[99],"key":[101],"modules:":[102],"Dissonance":[103],"for":[105,111,146,156],"Vacuity":[109],"Extensive":[114],"experiments":[115],"demonstrate":[116],"outperforms":[119],"state-of-the-art":[120],"methods":[121],"across":[122],"multiple":[123],"metrics":[124],"tasks":[127],"classification,":[130],"detection,":[132],"demonstrates":[137],"necessity":[139],"uncertainty":[141],"estimation":[142],"logical":[144],"reasoning":[145],"paves":[153],"way":[155],"open-world":[157],"learning.":[159],"Our":[160],"code":[161],"available":[165],"at":[166],"https://github.com/SSSKJ/EviNET.":[167]},"counts_by_year":[],"updated_date":"2026-05-05T06:06:40.768181","created_date":"2025-08-01T00:00:00"}