{"id":"https://openalex.org/W4367046771","doi":"https://doi.org/10.1145/3543507.3583386","title":"GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks","display_name":"GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367046771","doi":"https://doi.org/10.1145/3543507.3583386"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583386","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583386","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 ACM Web Conference 2023","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583386","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030809906","display_name":"Zemin Liu","orcid":"https://orcid.org/0000-0001-6262-9435"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Zemin Liu","raw_affiliation_strings":["National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048717995","display_name":"Xingtong Yu","orcid":"https://orcid.org/0000-0002-2884-8578"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingtong Yu","raw_affiliation_strings":["University of Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055103025","display_name":"Yuan Fang","orcid":"https://orcid.org/0000-0002-4265-5289"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yuan Fang","raw_affiliation_strings":["Singapore Management University, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002162759","display_name":"Xinming Zhang","orcid":"https://orcid.org/0000-0002-8136-6834"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinming Zhang","raw_affiliation_strings":["University of Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030809906"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":25.9243,"has_fulltext":true,"cited_by_count":150,"citation_normalized_percentile":{"value":0.99730571,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"417","last_page":"428"},"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":0.984499990940094,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9812999963760376,"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/computer-science","display_name":"Computer science","score":0.7327655553817749},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6092687845230103},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5637340545654297},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.4980354309082031},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4597201347351074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4235849380493164},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23464804887771606},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08259573578834534}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7327655553817749},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6092687845230103},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5637340545654297},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.4980354309082031},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4597201347351074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4235849380493164},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23464804887771606},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08259573578834534},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543507.3583386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583386","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583386","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 ACM Web Conference 2023","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3543507.3583386","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583386","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583386","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 ACM Web Conference 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4174942544","display_name":null,"funder_award_id":"T2EP20122-0041","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"},{"id":"https://openalex.org/G5016601650","display_name":null,"funder_award_id":"Academic Research Fund","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"},{"id":"https://openalex.org/G6854926366","display_name":null,"funder_award_id":"Tier 2","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"},{"id":"https://openalex.org/G901625343","display_name":null,"funder_award_id":"Academic Research F","funder_id":"https://openalex.org/F4320320751","funder_display_name":"Ministry of Education - Singapore"}],"funders":[{"id":"https://openalex.org/F4320320751","display_name":"Ministry of Education - Singapore","ror":"https://ror.org/01kcva023"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367046771.pdf","grobid_xml":"https://content.openalex.org/works/W4367046771.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2099438806","https://openalex.org/W2154851992","https://openalex.org/W2788919350","https://openalex.org/W2811124557","https://openalex.org/W2907492528","https://openalex.org/W2951659295","https://openalex.org/W2962756421","https://openalex.org/W2963066159","https://openalex.org/W2963224980","https://openalex.org/W2970771982","https://openalex.org/W2984323660","https://openalex.org/W2998496395","https://openalex.org/W3012816161","https://openalex.org/W3036446966","https://openalex.org/W3042563449","https://openalex.org/W3080997787","https://openalex.org/W3093957844","https://openalex.org/W3095602948","https://openalex.org/W3099152386","https://openalex.org/W3100807776","https://openalex.org/W3104097132","https://openalex.org/W3153329411","https://openalex.org/W3168406300","https://openalex.org/W3172133997","https://openalex.org/W3173421061","https://openalex.org/W3174146526","https://openalex.org/W4287121295","https://openalex.org/W4290877635","https://openalex.org/W4292779060","https://openalex.org/W6778883912","https://openalex.org/W6779490673","https://openalex.org/W6784694379"],"related_works":["https://openalex.org/W1583765404","https://openalex.org/W4214653257","https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2055438207","https://openalex.org/W2521424917","https://openalex.org/W3040203686","https://openalex.org/W2810751659","https://openalex.org/W4249524554","https://openalex.org/W258997015"],"abstract_inverted_index":{"Graphs":[0],"can":[1],"model":[2,163],"complex":[3],"relationships":[4],"between":[5,87],"objects,":[6],"enabling":[7],"a":[8,29,46,71,93,107,122,139,146,151,165],"myriad":[9],"of":[10,49,99],"Web":[11],"applications":[12],"such":[13],"as":[14,28],"online":[15],"page/article":[16],"classification":[17],"and":[18,59,89,125,135,179],"social":[19],"recommendation.":[20],"While":[21],"graph":[22,33],"neural":[23],"networks":[24],"(GNNs)":[25],"have":[26,63],"emerged":[27],"powerful":[30],"tool":[31],"for":[32],"representation":[34],"learning,":[35],"in":[36,76,92,154,164],"an":[37],"end-to-end":[38],"supervised":[39],"setting,":[40],"their":[41],"performance":[42],"heavily":[43],"relies":[44],"on":[45,101,128,173],"large":[47],"amount":[48],"task-specific":[50,94,166],"supervision.":[51],"To":[52],"reduce":[53],"labeling":[54],"requirement,":[55],"the":[56,85,156,161],"\u201cpre-train,":[57,60],"fine-tune\u201d":[58],"prompt\u201d":[61],"paradigms":[62],"become":[64],"increasingly":[65],"common.":[66],"In":[67,116],"particular,":[68],"prompting":[69,100,126],"is":[70,81,103],"popular":[72],"alternative":[73],"to":[74,83,110,112,149,177],"fine-tuning":[75],"natural":[77],"language":[78],"processing,":[79],"which":[80],"designed":[82],"narrow":[84],"gap":[86],"pre-training":[88,124,134],"downstream":[90,114,136,152],"objectives":[91],"manner.":[95,167],"However,":[96],"existing":[97],"study":[98],"graphs":[102],"still":[104],"limited,":[105],"lacking":[106],"universal":[108],"treatment":[109],"appeal":[111],"different":[113],"tasks.":[115],"this":[117],"paper,":[118],"we":[119,169],"propose":[120],"GraphPrompt,":[121],"novel":[123],"framework":[127],"graphs.":[129],"GraphPrompt":[130],"not":[131],"only":[132],"unifies":[133],"tasks":[137],"into":[138],"common":[140],"task":[141,153],"template,":[142],"but":[143],"also":[144],"employs":[145],"learnable":[147],"prompt":[148],"assist":[150],"locating":[155],"most":[157],"relevant":[158],"knowledge":[159],"from":[160],"pre-trained":[162],"Finally,":[168],"conduct":[170],"extensive":[171],"experiments":[172],"five":[174],"public":[175],"datasets":[176],"evaluate":[178],"analyze":[180],"GraphPrompt.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":75},{"year":2024,"cited_by_count":58},{"year":2023,"cited_by_count":7}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
