{"id":"https://openalex.org/W4406611454","doi":"https://doi.org/10.1109/smc54092.2024.10831558","title":"GraDiNet: Implicit Self-Distillation of Graph Structural Knowledge","display_name":"GraDiNet: Implicit Self-Distillation of Graph Structural Knowledge","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406611454","doi":"https://doi.org/10.1109/smc54092.2024.10831558"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5043282426","display_name":"Junyan Xu","orcid":"https://orcid.org/0000-0002-3789-2319"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Junyan Xu","raw_affiliation_strings":["ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110"],"affiliations":[{"raw_affiliation_string":"ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073845819","display_name":"Jianxing Liao","orcid":"https://orcid.org/0009-0002-5474-4163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianxing Liao","raw_affiliation_strings":["ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110"],"affiliations":[{"raw_affiliation_string":"ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025220345","display_name":"Rucong Xu","orcid":"https://orcid.org/0000-0003-3872-2255"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rucong Xu","raw_affiliation_strings":["ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110"],"affiliations":[{"raw_affiliation_string":"ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101793983","display_name":"Yun Li","orcid":"https://orcid.org/0000-0002-7628-0358"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun Li","raw_affiliation_strings":["ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110"],"affiliations":[{"raw_affiliation_string":"ShenZhen Institute for Advanced Study, University of Electronic Science and Technology of China,Shenzhen,China,518110","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043282426"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23339087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4930","last_page":"4935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9902999997138977,"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":0.9902999997138977,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9444000124931335,"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":0.7117542028427124},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6377147436141968},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5231351256370544},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5034684538841248},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.43029603362083435},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38653457164764404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30289024114608765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17518678307533264},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.15201157331466675},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07333874702453613},{"id":"https://openalex.org/keywords/organic-chemistry","display_name":"Organic chemistry","score":0.06011158227920532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7117542028427124},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6377147436141968},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5231351256370544},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5034684538841248},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.43029603362083435},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38653457164764404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30289024114608765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17518678307533264},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.15201157331466675},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07333874702453613},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.06011158227920532}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2341518610","display_name":null,"funder_award_id":"2021B1515120078","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6756071892","display_name":null,"funder_award_id":"92270105","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1503428008","https://openalex.org/W2168190036","https://openalex.org/W2766585573","https://openalex.org/W2907492528","https://openalex.org/W2922364443","https://openalex.org/W2992308087","https://openalex.org/W3011667710","https://openalex.org/W3034795332","https://openalex.org/W3080083111","https://openalex.org/W3152626252","https://openalex.org/W3192084854","https://openalex.org/W4231449374","https://openalex.org/W4313639623","https://openalex.org/W4366463135","https://openalex.org/W4392979548","https://openalex.org/W4402352127","https://openalex.org/W6702752216","https://openalex.org/W6726873649","https://openalex.org/W6802881785"],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W2344382886","https://openalex.org/W19111321","https://openalex.org/W2412887479","https://openalex.org/W32245304","https://openalex.org/W2532801570","https://openalex.org/W4385627933","https://openalex.org/W2480127678","https://openalex.org/W2806270048","https://openalex.org/W4310605282"],"abstract_inverted_index":{"Graph":[0,28],"Knowledge":[1],"Distillation":[2],"(GKD)":[3],"in":[4,126],"artificial":[5],"intelligence":[6],"typically":[7],"employs":[8],"a":[9,27,32,40,78,89,96,123],"teacher-student":[10],"model,":[11],"which":[12],"faces":[13],"challenges":[14],"such":[15],"as":[16],"rigidity,":[17],"time-consumption,":[18],"and":[19,50,67,81,95,110,154,170],"teacher":[20,41,125],"training.":[21],"To":[22],"improve,":[23],"this":[24,150],"paper":[25],"develops":[26],"self-Distillation":[29],"Network":[30],"(GraDiNet),":[31],"framework":[33],"that":[34,141],"operates":[35],"without":[36],"the":[37,62,68,85,100,106,120,155],"need":[38],"for":[39,122],"model":[42],"or":[43],"graph":[44,128],"neural":[45],"network":[46],"(GNN)":[47],"during":[48],"training":[49,101],"inferencing":[51],"phases.":[52],"GraDiNet":[53,86,115,159],"uniquely":[54],"utilizes":[55],"multi-layer":[56],"perceptrons":[57],"(MLPs)":[58],"to":[59,103,118,133],"harness":[60],"both":[61],"structural":[63],"knowledge":[64,130],"of":[65,71,165],"graphs":[66],"semantic":[69],"information":[70],"nodes,":[72],"thus":[73,160],"facilitating":[74],"hierarchical":[75,152],"self-distillation":[76,153],"between":[77,108],"target":[79],"node":[80,135],"its":[82],"neighbors.":[83],"Additionally,":[84],"approach":[87],"incorporates":[88],"novel":[90],"similarity-based":[91],"difference":[92,157],"enhancement":[93],"technique":[94],"penalty":[97],"factor":[98],"within":[99],"loss":[102],"further":[104],"delineate":[105],"distinction":[107],"positive":[109],"negative":[111],"samples.":[112],"This":[113],"allows":[114],"not":[116],"only":[117],"bypass":[119],"necessity":[121],"GNN":[124],"learning":[127],"structure":[129],"but":[131],"also":[132],"predict":[134],"classification":[136],"efficiently.":[137],"Extensive":[138],"evaluations":[139],"show":[140],"standard":[142],"MLPs":[143,169],"can":[144],"significantly":[145],"boost":[146],"their":[147],"performance":[148],"through":[149],"implicit":[151],"similarity":[156],"enhancement.":[158],"achieves":[161],"an":[162],"average":[163],"improvement":[164],"15%":[166],"over":[167],"conventional":[168],"outperforms":[171],"leading":[172],"state-of-the-art":[173],"GKD":[174],"methods":[175],"across":[176],"three":[177],"real-world":[178],"datasets.":[179]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
