{"id":"https://openalex.org/W4401857173","doi":"https://doi.org/10.1145/3637528.3671987","title":"HiGPT: Heterogeneous Graph Language Model","display_name":"HiGPT: Heterogeneous Graph Language Model","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401857173","doi":"https://doi.org/10.1145/3637528.3671987"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5101451300","display_name":"Jiabin Tang","orcid":"https://orcid.org/0009-0002-7002-3585"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Jiabin Tang","raw_affiliation_strings":["University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024168844","display_name":"Yuhao Yang","orcid":"https://orcid.org/0000-0002-2543-8450"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuhao Yang","raw_affiliation_strings":["University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014213168","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0002-6653-3788"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wei Wei","raw_affiliation_strings":["University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103324122","display_name":"Lei Shi","orcid":"https://orcid.org/0009-0008-8043-7224"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Shi","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058689010","display_name":"\u9686\u7fa9 \u5c71\u4e0b","orcid":"https://orcid.org/0000-0002-3016-4351"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Xia","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101771060","display_name":"Dawei Yin","orcid":"https://orcid.org/0000-0002-0684-6205"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Yin","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091518548","display_name":"Chao Huang","orcid":"https://orcid.org/0009-0003-3740-4500"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chao Huang","raw_affiliation_strings":["University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101451300"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":10.7154,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.98650895,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2842","last_page":"2853"},"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":0.9991999864578247,"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":0.9919000267982483,"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":0.7426625490188599},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46105849742889404},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.38129112124443054},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2740052044391632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7426625490188599},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46105849742889404},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.38129112124443054},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2740052044391632}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W2624431344","https://openalex.org/W2743104969","https://openalex.org/W2951626319","https://openalex.org/W2965857891","https://openalex.org/W2970398671","https://openalex.org/W2970641574","https://openalex.org/W2997686727","https://openalex.org/W3004507689","https://openalex.org/W3012871709","https://openalex.org/W3042563449","https://openalex.org/W3044421346","https://openalex.org/W3103513278","https://openalex.org/W3108202858","https://openalex.org/W3111359424","https://openalex.org/W3117136530","https://openalex.org/W3135367836","https://openalex.org/W3155886566","https://openalex.org/W3167292670","https://openalex.org/W3172710079","https://openalex.org/W3175971420","https://openalex.org/W3207553988","https://openalex.org/W4212931205","https://openalex.org/W4221143046","https://openalex.org/W4285378361","https://openalex.org/W4287717240","https://openalex.org/W4290927951","https://openalex.org/W4290948206","https://openalex.org/W4292423649","https://openalex.org/W4307010406","https://openalex.org/W4316829903","https://openalex.org/W4321452549","https://openalex.org/W4376864968","https://openalex.org/W4377130677","https://openalex.org/W4382317738","https://openalex.org/W4383982659","https://openalex.org/W4385567149","https://openalex.org/W4385571831","https://openalex.org/W6745537798","https://openalex.org/W6758105487"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Heterogeneous":[0],"graph":[1,17,30,55,64,99,131,135,167,187,207],"learning":[2,56,107,141],"aims":[3],"to":[4,18,84,86,101,104,195,218],"capture":[5],"complex":[6,198],"relationships":[7,172],"and":[8,24,42,47,73,88,117,201,225],"diverse":[9,62,105,224],"relational":[10],"semantics":[11],"among":[12],"entities":[13],"in":[14,28,59,112,160,173,232,241],"a":[15,128,182],"heterogeneous":[16,29,54,63,98,144,166,175],"obtain":[19],"meaningful":[20],"representations":[21],"for":[22,53,149],"nodes":[23],"edges.":[25],"Recent":[26],"advancements":[27],"neural":[31],"networks":[32],"(HGNNs)":[33],"have":[34,57],"achieved":[35],"state-of-the-art":[36],"performance":[37,240],"by":[38,222],"considering":[39],"relation":[40,118,199],"heterogeneity":[41,200],"using":[43],"specialized":[44],"message":[45],"functions":[46],"aggregation":[48],"rules.":[49],"However,":[50],"existing":[51],"frameworks":[52,69],"limitations":[58],"generalizing":[60],"across":[61],"datasets.":[65,155],"Most":[66],"of":[67,185,206,243],"these":[68],"follow":[70],"the":[71,77,93,147,193,212],"\"pre-train\"":[72],"\"fine-tune\"":[74],"paradigm":[75,217],"on":[76],"same":[78],"dataset,":[79],"which":[80],"restricts":[81],"their":[82],"capacity":[83],"adapt":[85],"new":[87],"unseen":[89],"data.":[90],"This":[91],"raises":[92],"question:":[94],"\"Can":[95],"we":[96,125,162,210],"generalize":[97],"models":[100],"be":[102],"well-adapted":[103],"downstream":[106,154],"tasks":[108],"with":[109,133,258],"distribution":[110,158],"shifts":[111,159],"both":[113],"node":[114],"token":[115],"sets":[116],"type":[119],"heterogeneity?\"":[120],"To":[121,156],"tackle":[122],"those":[123],"challenges,":[124],"propose":[126],"HiGPT,":[127,191],"general":[129],"large":[130,183],"model":[132,178,194,253],"<u>H</u>eterogeneous":[134],"<u>i</u>nstruction-tuning":[136],"paradigm.":[137],"Our":[138],"framework":[139,237],"enables":[140],"from":[142,153],"arbitrary":[143],"graphs":[145],"without":[146],"need":[148],"any":[150],"fine-tuning":[151],"process":[152],"handle":[157],"heterogeneity,":[161],"introduce":[163,211],"an":[164],"in-context":[165],"tokenizer":[168],"that":[169],"captures":[170],"semantic":[171],"different":[174],"graphs,":[176],"facilitating":[177],"adaptation.":[179],"We":[180,250],"incorporate":[181],"corpus":[184],"heterogeneity-aware":[186],"instructions":[188],"into":[189],"our":[190,235,252],"enabling":[192],"effectively":[196],"comprehend":[197],"distinguish":[202],"between":[203],"various":[204,233],"types":[205],"tokens.":[208],"Furthermore,":[209],"Mixture-of-Thought":[213],"(MoT)":[214],"instruction":[215],"augmentation":[216],"mitigate":[219],"data":[220],"scarcity":[221],"generating":[223],"informative":[226],"instructions.":[227],"Through":[228],"comprehensive":[229,259],"evaluations":[230],"conducted":[231],"settings,":[234],"proposed":[236],"demonstrates":[238],"exceptional":[239],"terms":[242],"generalization":[244],"performance,":[245],"surpassing":[246],"current":[247],"leading":[248],"benchmarks.":[249],"make":[251],"implementation":[254],"openly":[255],"available,":[256],"along":[257],"details":[260],"at:":[261],"https://github.com/HKUDS/HiGPT.":[262]},"counts_by_year":[{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}