{"id":"https://openalex.org/W4412376898","doi":"https://doi.org/10.1145/3726302.3730021","title":"Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs","display_name":"Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376898","doi":"https://doi.org/10.1145/3726302.3730021"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730021","doi":"https://doi.org/10.1145/3726302.3730021","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730021","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730021","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730021","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114054182","display_name":"Taiyan Zhang","orcid":"https://orcid.org/0009-0004-6757-9237","observed_orcids":["https://orcid.org/0009-0004-6757-9237"]},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]},{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Taiyan Zhang","raw_affiliation_strings":["ShanghaiTech University, Shanghai, China and Hong Kong Baptist University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0004-6757-9237","affiliations":[{"raw_affiliation_string":"ShanghaiTech University, Shanghai, China and Hong Kong Baptist University, Hong Kong, China","institution_ids":["https://openalex.org/I141568987","https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040420455","display_name":"Renchi Yang","orcid":"https://orcid.org/0000-0002-7284-3096","observed_orcids":["https://orcid.org/0000-0002-7284-3096"]},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Renchi Yang","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-7284-3096","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091763061","display_name":"Yurui Lai","orcid":"https://orcid.org/0009-0000-4402-3798","observed_orcids":["https://orcid.org/0009-0000-4402-3798"]},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yurui Lai","raw_affiliation_strings":["Hong Kong Baptist University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0000-4402-3798","affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University, Hong Kong, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004624509","display_name":"Mingyu Yan","orcid":"https://orcid.org/0000-0002-6915-955X","observed_orcids":["https://orcid.org/0000-0002-6915-955X"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyu Yan","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6915-955X","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023098180","display_name":"Xiaochun Ye","orcid":"https://orcid.org/0000-0003-4598-1685","observed_orcids":["https://orcid.org/0000-0003-4598-1685","https://orcid.org/0000-0002-0065-6128"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochun Ye","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4598-1685","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011407484","display_name":"Dongrui Fan","orcid":"https://orcid.org/0000-0001-5219-0908","observed_orcids":["https://orcid.org/0000-0001-5219-0908"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongrui Fan","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5219-0908","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9727,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.91139139,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"698","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"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":0.9990000128746033,"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":0.00019999999494757503,"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/T12072","display_name":"Machine Learning and Algorithms","score":9.999999747378752e-05,"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/text-attributed-graphs","display_name":"text-attributed graphs","score":0.9359999895095825},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9660000205039978},{"id":"https://openalex.org/keywords/active-learning-machine-learning","display_name":"active learning (machine learning)","score":0.656000018119812},{"id":"https://openalex.org/keywords/self-training","display_name":"self-training","score":0.8809999823570251},{"id":"https://openalex.org/keywords/pseudo-labeling","display_name":"pseudo-labeling","score":0.8510000109672546},{"id":"https://openalex.org/keywords/label-refinement","display_name":"label refinement","score":0.4950000047683716},{"id":"https://openalex.org/keywords/graph-rewiring","display_name":"graph rewiring","score":0.5350000262260437},{"id":"https://openalex.org/keywords/locle","display_name":"Locle","score":0.5770000219345093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.79599928855896},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6128180027008057},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5767089128494263},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.46919557452201843},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4347802400588989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41014358401298523},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3726302.3730021","doi":"https://doi.org/10.1145/3726302.3730021","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730021","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730021","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2412.11983","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.11983","pdf_url":"https://arxiv.org/pdf/2412.11983","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.11983","doi":"https://doi.org/10.48550/arxiv.2412.11983","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.11983","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3726302.3730021","doi":"https://doi.org/10.1145/3726302.3730021","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730021","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730021","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1702756715","display_name":null,"funder_award_id":"2022YFB4501400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G2881941594","display_name":null,"funder_award_id":"2022YFB4501400","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G3475438616","display_name":null,"funder_award_id":"62202451","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8618575630","display_name":null,"funder_award_id":"62302414","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/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335892","display_name":"Youth Innovation Promotion Association","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376898.pdf","grobid_xml":"https://content.openalex.org/works/W4412376898.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1548361610","https://openalex.org/W2119915772","https://openalex.org/W2124536061","https://openalex.org/W2125531986","https://openalex.org/W2125943921","https://openalex.org/W2162630660","https://openalex.org/W2168190036","https://openalex.org/W2294644361","https://openalex.org/W2798931143","https://openalex.org/W2896308983","https://openalex.org/W2964012239","https://openalex.org/W2970641574","https://openalex.org/W2995962548","https://openalex.org/W3035041376","https://openalex.org/W3126391297","https://openalex.org/W3156302073","https://openalex.org/W3172481377","https://openalex.org/W3173294575","https://openalex.org/W3185341429","https://openalex.org/W3191600673","https://openalex.org/W3201579042","https://openalex.org/W3208847423","https://openalex.org/W3210450783","https://openalex.org/W3215214493","https://openalex.org/W4226219101","https://openalex.org/W4285603626","https://openalex.org/W4367046776","https://openalex.org/W4376864968","https://openalex.org/W4381329639","https://openalex.org/W4382239329","https://openalex.org/W4382318469","https://openalex.org/W4393277515","https://openalex.org/W4396735838","https://openalex.org/W4400524696","https://openalex.org/W4401863467","https://openalex.org/W4403323657"],"related_works":["https://openalex.org/W4404781601","https://openalex.org/W2039871688","https://openalex.org/W2883491016","https://openalex.org/W4293279049","https://openalex.org/W3031069236","https://openalex.org/W2169518243","https://openalex.org/W2017214274","https://openalex.org/W1600005011","https://openalex.org/W4289128054","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"have":[4],"become":[5],"the":[6,48,206,220,234],"preferred":[7],"models":[8,28,53],"for":[9,39,68,127,156],"node":[10,69,153,216],"classification":[11],"in":[12,20,212,231],"graph":[13,22,196],"data":[14,38],"due":[15,87],"to":[16,45,59,80,88,139,165,210],"their":[17,61],"robust":[18],"capabilities":[19,64],"integrating":[21],"structures":[23],"and":[24,65,123,132,173,175,184],"attributes.":[25],"However,":[26],"these":[27,96],"heavily":[29],"depend":[30],"on":[31,170,192,219],"a":[32,55,160,177,187,237],"substantial":[33],"amount":[34],"of":[35,50,118,214,239],"high-quality":[36],"labeled":[37],"training,":[40],"which":[41],"is":[42,58,246],"often":[43],"costly":[44],"obtain.":[46],"With":[47],"rise":[49],"large":[51],"language":[52],"(LLMs),":[54],"promising":[56],"approach":[57,75],"utilize":[60],"exceptional":[62],"zero-shot":[63],"extensive":[66],"knowledge":[67],"labeling.":[70],"Despite":[71],"encouraging":[72],"results,":[73],"this":[74],"either":[76],"requires":[77],"numerous":[78],"queries":[79],"LLMs":[81,111,131,183,211],"or":[82],"suffers":[83],"from":[84],"reduced":[85],"performance":[86],"noisy":[89],"labels":[90],"generated":[91],"by":[92],"LLMs.":[93],"To":[94],"address":[95],"challenges,":[97],"we":[98],"introduce":[99],"Locle,":[100],"an":[101,150,228],"active":[102,152],"self-training":[103],"framework":[104],"that":[105,181,199],"does":[106],"Label-free":[107],"nOde":[108],"Classification":[109],"with":[110,129,186,223],"cost-Effectively.":[112],"Locle":[113,144,200,226],"iteratively":[114],"identifies":[115],"small":[116],"sets":[117],"''critical''":[119,167],"samples":[120],"using":[121],"GNNs":[122,185],"extracts":[124],"informative":[125],"pseudo-labels":[126],"them":[128],"both":[130],"GNNs,":[133],"serving":[134],"as":[135],"additional":[136],"supervision":[137],"signals":[138],"enhance":[140],"model":[141],"training.":[142],"Specifically,":[143],"comprises":[145],"three":[146],"key":[147],"components:":[148],"(i)":[149],"effective":[151],"selection":[154,163],"strategy":[155],"initial":[157],"annotations;":[158],"(ii)":[159],"careful":[161],"sample":[162],"scheme":[164],"identify":[166],"nodes":[168],"based":[169],"label":[171,178],"disharmonicity":[172],"entropy;":[174],"(iii)":[176],"refinement":[179],"module":[180],"combines":[182],"rewired":[188],"topology.":[189],"Extensive":[190],"experiments":[191],"five":[193],"benchmark":[194],"text-attributed":[195],"datasets":[197],"demonstrate":[198],"significantly":[201],"outperforms":[202],"state-of-the-art":[203,235],"methods":[204],"under":[205],"same":[207],"query":[208],"budget":[209],"terms":[213],"label-free":[215],"classification.":[217],"Notably,":[218],"DBLP":[221],"dataset":[222],"14.3k":[224],"nodes,":[225],"achieves":[227],"8.08%":[229],"improvement":[230],"accuracy":[232],"over":[233],"at":[236,248],"cost":[238],"less":[240],"than":[241],"one":[242],"cent.":[243],"Our":[244],"code":[245],"available":[247],"https://github.com/HKBU-LAGAS/Locle.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}