{"id":"https://openalex.org/W7160030694","doi":"https://doi.org/10.48550/arxiv.2605.00731","title":"Empowering Heterogeneous Graph Foundation Models via Decoupled Relation Alignment","display_name":"Empowering Heterogeneous Graph Foundation Models via Decoupled Relation Alignment","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7160030694","doi":"https://doi.org/10.48550/arxiv.2605.00731"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.00731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00731","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.00731","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135119154","display_name":"Ziyu Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Ziyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135257316","display_name":"Yaming Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yaming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135148722","display_name":"Zhe Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135122895","display_name":"Ziyu Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Ziyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135216399","display_name":"Wei Zhao","orcid":"https://orcid.org/0000-0003-1414-4438"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9815000295639038,"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":0.9815000295639038,"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":0.007300000172108412,"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"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/relation","display_name":"Relation (database)","score":0.6287999749183655},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5939000248908997},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5527999997138977},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5303999781608582},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5270000100135803},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4991999864578247},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4253000020980835},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.42160001397132874},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.40119999647140503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6437000036239624},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6287999749183655},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.6039000153541565},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5939000248908997},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5527999997138977},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5270000100135803},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4991999864578247},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4253000020980835},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.42160001397132874},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.40119999647140503},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3935000002384186},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3928000032901764},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2782000005245209},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25870001316070557},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.00731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00731","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.00731","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00731","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"Graph":[1],"Foundation":[2],"Models":[3],"(GFMs)":[4],"have":[5],"achieved":[6],"remarkable":[7],"success":[8],"in":[9],"homogeneous":[10],"graphs,":[11],"extending":[12],"them":[13],"to":[14,24,56,100,118],"multi-domain":[15],"heterogeneous":[16],"graphs":[17],"(MDHGs)":[18],"remains":[19],"a":[20,41,74,95,105,112,123,128,138,150,170],"formidable":[21],"challenge":[22],"due":[23],"cross-type":[25,102],"feature":[26,34,43,87],"shifts":[27,82],"and":[28,50,59,127,175,180],"intra-domain":[29,134],"relation":[30,70,90,108],"gaps.":[31],"Existing":[32],"global":[33],"alignment":[35,78],"methods":[36],"(PCA":[37],"or":[38],"SVD)":[39],"enforce":[40],"shared":[42,106],"space":[44],"blindly,":[45],"which":[46],"distorts":[47],"type-specific":[48],"semantics":[49,88],"disrupts":[51],"original":[52],"topologies,":[53],"inevitably":[54],"leading":[55],"\"Type":[57],"Collapse\"":[58],"\"Relation":[60],"Confusion\".":[61],"To":[62],"address":[63],"these":[64],"fundamental":[65],"limitations,":[66],"we":[67],"propose":[68],"Decoupled":[69],"Subspace":[71],"Alignment":[72],"(DRSA),":[73],"novel,":[75],"plug-and-play":[76],"relation-driven":[77],"framework.":[79],"DRSA":[80,148,164],"fundamentally":[81],"the":[83,178],"paradigm":[84],"by":[85],"decoupling":[86],"from":[89],"structures.":[91],"Specifically,":[92],"it":[93],"introduces":[94],"dual-relation":[96],"subspace":[97,109],"projection":[98,125],"mechanism":[99],"coordinate":[101],"interactions":[103],"within":[104],"low-rank":[107],"explicitly.":[110],"Furthermore,":[111],"feature-structure":[113],"decoupled":[114],"representation":[115],"is":[116,190],"designed":[117],"decompose":[119],"aligned":[120],"features":[121],"into":[122],"semantic":[124],"component":[126],"structural":[129],"residual":[130],"term,":[131],"adaptively":[132],"absorbing":[133],"variations.":[135],"Optimized":[136],"via":[137],"stable":[139],"alternating":[140],"minimization":[141],"strategy":[142],"based":[143],"on":[144,157],"Block":[145],"Coordinate":[146],"Descent,":[147],"constructs":[149],"well-calibrated,":[151],"structure-aware":[152],"latent":[153],"space.":[154],"Extensive":[155],"experiments":[156],"multiple":[158],"real-world":[159],"benchmark":[160],"datasets":[161],"demonstrate":[162],"that":[163],"can":[165],"be":[166],"seamlessly":[167],"integrated":[168],"as":[169],"universal":[171],"preprocessing":[172],"module,":[173],"significantly":[174],"consistently":[176],"enhancing":[177],"cross-domain":[179],"few-shot":[181],"knowledge":[182],"transfer":[183],"capabilities":[184],"of":[185],"state-of-the-art":[186],"GFMs.":[187],"The":[188],"code":[189],"available":[191],"at:":[192],"https://github.com/zhengziyu77/DSRA.":[193]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-05T00:00:00"}
