{"id":"https://openalex.org/W4400680366","doi":"https://doi.org/10.1109/tnnls.2024.3420895","title":"Fine-Grained Learning Behavior-Oriented Knowledge Distillation for Graph Neural Networks","display_name":"Fine-Grained Learning Behavior-Oriented Knowledge Distillation for Graph Neural Networks","publication_year":2024,"publication_date":"2024-07-16","ids":{"openalex":"https://openalex.org/W4400680366","doi":"https://doi.org/10.1109/tnnls.2024.3420895","pmid":"https://pubmed.ncbi.nlm.nih.gov/39012738"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3420895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3420895","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100509393","display_name":"Kang Liu","orcid":"https://orcid.org/0000-0002-9447-7111"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Liu","raw_affiliation_strings":["School of Computer Science, South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9447-7111","affiliations":[{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049015061","display_name":"Zhenhua Huang","orcid":"https://orcid.org/0000-0001-8659-4062"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Huang","raw_affiliation_strings":["School of Computer Science, South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8659-4062","affiliations":[{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076335744","display_name":"Chang\u2010Dong Wang","orcid":"https://orcid.org/0000-0001-5972-559X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang-Dong Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5972-559X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101966362","display_name":"Beibei Gao","orcid":"https://orcid.org/0000-0002-1441-0583"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beibei Gao","raw_affiliation_strings":["School of Philosophy and Social Development, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Philosophy and Social Development, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022951772","display_name":"Yunwen Chen","orcid":"https://orcid.org/0000-0002-7493-5672"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunwen Chen","raw_affiliation_strings":["Research and Development Department, DataGrand Inc., Shanghai, China","Research and Development Department, DataGrand Inc, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7493-5672","affiliations":[{"raw_affiliation_string":"Research and Development Department, DataGrand Inc., Shanghai, China","institution_ids":[]},{"raw_affiliation_string":"Research and Development Department, DataGrand Inc, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2495,"currency":"USD","value_usd":2495},"apc_paid":null,"fwci":4.1468,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94483961,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"36","issue":"5","first_page":"9422","last_page":"9436"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965000152587891,"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":0.9965000152587891,"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/T11122","display_name":"Online Learning and Analytics","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7202266454696655},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6267276406288147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5763172507286072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5350704193115234},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5023400783538818},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4520948529243469},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4461562931537628},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44279274344444275},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14609986543655396},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.13811403512954712},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07662022113800049}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7202266454696655},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6267276406288147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763172507286072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5350704193115234},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5023400783538818},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4520948529243469},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4461562931537628},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44279274344444275},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14609986543655396},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.13811403512954712},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07662022113800049},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3420895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3420895","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:39012738","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39012738","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1280930457","display_name":null,"funder_award_id":"2022B1515120059","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G2609543366","display_name":null,"funder_award_id":"2022A1515011380","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G3159983421","display_name":null,"funder_award_id":"62276277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G77659056","display_name":null,"funder_award_id":"62172166","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8468595616","display_name":"\u57fa\u4e8e\u77e5\u8bc6\u56fe\u8c31\u7684\u793e\u4ea4\u5a92\u4f53\u5927\u6570\u636e\u4e3b\u9898\u53d1\u73b0\u4e0e\u8d8b\u52bf\u9884\u6d4b\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"61772366","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/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1821462560","https://openalex.org/W1991418309","https://openalex.org/W2116341502","https://openalex.org/W2141585940","https://openalex.org/W2145979309","https://openalex.org/W2168190036","https://openalex.org/W2907492528","https://openalex.org/W2963140444","https://openalex.org/W3007662311","https://openalex.org/W3034795332","https://openalex.org/W3152626252","https://openalex.org/W3174102142","https://openalex.org/W3177196641","https://openalex.org/W3177378457","https://openalex.org/W3189898989","https://openalex.org/W3198025215","https://openalex.org/W3212385273","https://openalex.org/W4205581758","https://openalex.org/W4224324119","https://openalex.org/W4226426325","https://openalex.org/W4281560842","https://openalex.org/W4282970521","https://openalex.org/W4282975557","https://openalex.org/W4285138331","https://openalex.org/W4285258280","https://openalex.org/W4292948016","https://openalex.org/W4311511747","https://openalex.org/W4312910076","https://openalex.org/W4318718201","https://openalex.org/W4318774130","https://openalex.org/W4321372691","https://openalex.org/W4365393360","https://openalex.org/W4376125564","https://openalex.org/W4382202907","https://openalex.org/W4382239191","https://openalex.org/W4382239927","https://openalex.org/W4382458595","https://openalex.org/W4385486149","https://openalex.org/W4385612609","https://openalex.org/W4385687011","https://openalex.org/W4386914148","https://openalex.org/W4387790227","https://openalex.org/W4387846639","https://openalex.org/W4388966790","https://openalex.org/W4390604335","https://openalex.org/W4390908058","https://openalex.org/W4392384432","https://openalex.org/W4392796768","https://openalex.org/W6637551013","https://openalex.org/W6680380971","https://openalex.org/W6684391652","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6757639898","https://openalex.org/W6766978945","https://openalex.org/W6776488958","https://openalex.org/W6781932242","https://openalex.org/W6802881785","https://openalex.org/W6841989129","https://openalex.org/W6842607031","https://openalex.org/W6846657290","https://openalex.org/W6852990246","https://openalex.org/W6855082141"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372","https://openalex.org/W3099502074"],"abstract_inverted_index":{"Knowledge":[0],"distillation":[1,50],"(KD),":[2],"as":[3],"an":[4],"effective":[5],"compression":[6],"technology,":[7],"is":[8],"used":[9],"to":[10,108,121],"reduce":[11],"the":[12,35,81,85,106,116,145,153],"resource":[13],"consumption":[14],"of":[15,37,84,149],"graph":[16],"neural":[17],"networks":[18],"(GNNs)":[19],"and":[20,33,40,47,72,94,101,136,147],"facilitate":[21],"their":[22],"deployment":[23],"on":[24,30,49,111],"resource-constrained":[25],"devices.":[26],"Numerous":[27],"studies":[28],"exist":[29],"GNN":[31],"distillation,":[32],"however,":[34],"impacts":[36],"knowledge":[38,69,99],"complexity":[39],"differences":[41],"in":[42,128],"learning":[43,61,74,102,119],"behavior":[44,62,75],"between":[45],"teachers":[46],"students":[48],"efficiency":[51,103],"remain":[52],"underexplored.":[53],"We":[54],"propose":[55],"a":[56],"KD":[57],"method":[58],"for":[59,125],"fine-grained":[60],"(FLB),":[63],"comprising":[64],"two":[65,89],"main":[66],"components:":[67],"feature":[68],"decoupling":[70],"(FKD)":[71],"teacher":[73,117],"guidance":[76,124],"(TLBG).":[77],"Specifically,":[78],"FKD":[79],"decouples":[80],"intermediate-layer":[82],"features":[83,92,96],"student":[86,107,129,150],"network":[87],"into":[88],"types:":[90],"teacher-related":[91],"(TRFs)":[93],"downstream":[95],"(DFs),":[97],"enhancing":[98],"comprehension":[100],"by":[104],"guiding":[105],"simultaneously":[109],"focus":[110],"these":[112],"features.":[113],"TLBG":[114],"maps":[115],"model's":[118],"behaviors":[120],"provide":[122],"reliable":[123],"correcting":[126],"deviations":[127],"learning.":[130],"Extensive":[131],"experiments":[132],"across":[133],"eight":[134],"datasets":[135],"12":[137],"baseline":[138],"frameworks":[139],"demonstrate":[140],"that":[141],"FLB":[142],"significantly":[143],"enhances":[144],"performance":[146],"robustness":[148],"GNNs":[151],"within":[152],"original":[154],"framework.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":9}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}