{"id":"https://openalex.org/W7130531349","doi":"https://doi.org/10.1109/tkde.2026.3666242","title":"ARLIE: Adaptive Reinforcement Learning With Inductive Embeddings for Fully-Inductive Multi-Hop Reasoning Over Temporal Knowledge Graphs","display_name":"ARLIE: Adaptive Reinforcement Learning With Inductive Embeddings for Fully-Inductive Multi-Hop Reasoning Over Temporal Knowledge Graphs","publication_year":2026,"publication_date":"2026-02-19","ids":{"openalex":"https://openalex.org/W7130531349","doi":"https://doi.org/10.1109/tkde.2026.3666242"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2026.3666242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3666242","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-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/A5126409168","display_name":"Shangfei Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangfei Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7286-5631","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126395986","display_name":"Yunjun Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjun Gao","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3816-8450","affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"An Liu","orcid":"https://orcid.org/0000-0002-6368-576X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An Liu","raw_affiliation_strings":["School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6368-576X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126442166","display_name":"Wenhao Li","orcid":null},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Li","raw_affiliation_strings":["School of Information Science and Engineering, Shandong Normal University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-3642-2999","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong Normal University, Jinan, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126412376","display_name":"Tong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tong Chen","raw_affiliation_strings":["School of ITEE, The University of Queensland, St Lucia, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7269-146X","affiliations":[{"raw_affiliation_string":"School of ITEE, The University of Queensland, St Lucia, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122317769","display_name":"Hongzhi Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hongzhi Yin","raw_affiliation_strings":["School of ITEE, The University of Queensland, St Lucia, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0003-1395-261X","affiliations":[{"raw_affiliation_string":"School of ITEE, The University of Queensland, St Lucia, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22185093,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"5","first_page":"2587","last_page":"2601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8989999890327454,"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":0.8989999890327454,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.02459999918937683,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.01759999990463257,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7152000069618225},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5586000084877014},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5400999784469604},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45809999108314514},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41940000653266907},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.4154999852180481},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.3926999866962433},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.3659999966621399}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7983999848365784},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7152000069618225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995000243186951},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5586000084877014},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5400999784469604},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.436599999666214},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.4154999852180481},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C197352929","wikidata":"https://www.wikidata.org/wiki/Q1074074","display_name":"Inductive bias","level":4,"score":0.36250001192092896},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2779382394","wikidata":"https://www.wikidata.org/wiki/Q1464197","display_name":"Inductive logic programming","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C521332185","wikidata":"https://www.wikidata.org/wiki/Q185816","display_name":"Analogy","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.25360000133514404},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2026.3666242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3666242","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7826454043388367,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1291028582","display_name":null,"funder_award_id":"62402447","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Temporal":[0],"knowledge":[1,29],"graphs":[2],"(TKGs)":[3],"effectively":[4],"capture":[5],"the":[6,20,42,60,74,90,102,162],"dynamic":[7],"evolution":[8,188],"of":[9,22,45,105,146,161,192],"events":[10],"over":[11,156,208],"time,":[12],"emerging":[13],"as":[14],"a":[15,142],"critical":[16],"driving":[17],"force":[18],"in":[19,89,110,150],"advancement":[21],"artificial":[23],"intelligence.":[24],"In":[25],"recent":[26],"years,":[27],"temporal":[28,187],"graph":[30],"reasoning":[31,55,68,114,127,149],"(TKGR)":[32],"has":[33],"garnered":[34],"significant":[35],"attention":[36],"for":[37,73,176],"its":[38],"ability":[39],"to":[40,59,120,203],"address":[41,130],"intrinsic":[43],"incompleteness":[44],"TKGs.":[46,157,209],"Among":[47],"various":[48],"TKGR":[49,218],"methods,":[50],"reinforcement":[51],"learning":[52],"(RL)-based":[53],"multi-hop":[54,67,113,148],"stands":[56],"out":[57],"due":[58],"decision-making":[61],"capabilities":[62],"and":[63,84,95,153,189,223],"interpretability.":[64],"However,":[65],"existing":[66],"methods":[69,115,219],"are":[70,80,98],"predominantly":[71],"designed":[72],"transductive":[75,154,224],"setting":[76,92],"where":[77,93],"test":[78,96],"entities":[79,97,109,178],"observed":[81],"during":[82],"training,":[83],"they":[85],"exhibit":[86],"limited":[87],"performance":[88],"fully-inductive":[91,152,222],"training":[94],"entirely":[99],"disjoint.":[100],"Moreover,":[101],"sparse":[103],"links":[104],"newly":[106],"emerged":[107],"unseen":[108,177,193],"TKGs":[111],"hinder":[112],"from":[116],"utilizing":[117],"sufficient":[118],"actions":[119,202],"construct":[121],"multihop":[122],"relational":[123],"paths,":[124],"ultimately":[125],"impairing":[126],"accuracy.":[128],"To":[129],"these":[131],"challenges,":[132],"we":[133],"propose":[134],"ARLIE":[135,159,215],"(Adaptive":[136],"Reinforcement":[137],"Learning":[138],"with":[139],"Inductive":[140],"Embeddings),":[141],"novel":[143],"method":[144,172],"capable":[145],"conducting":[147],"both":[151,221],"settings":[155],"Specifically,":[158],"consists":[160],"following":[163],"two":[164],"key":[165],"components.":[166],"(1)":[167],"A":[168],"context-based":[169],"inductive":[170],"representation":[171],"generates":[173],"finegrained":[174],"embeddings":[175],"by":[179],"exploiting":[180],"queryrelated":[181],"contextual":[182],"information.":[183],"(2)":[184],"After":[185],"obtaining":[186],"semantic":[190],"dependencies":[191],"entities,":[194],"an":[195],"actionaugmented":[196],"adaptive":[197],"RL":[198],"framework":[199],"leverages":[200],"diverse":[201],"infer":[204],"missing":[205],"elements":[206],"step-by-step":[207],"Finally,":[210],"experimental":[211],"results":[212],"show":[213],"that":[214],"surpasses":[216],"state-of-the-art":[217],"across":[220],"settings.":[225]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-20T00:00:00"}