{"id":"https://openalex.org/W7156137445","doi":"https://doi.org/10.48550/arxiv.2604.22031","title":"Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning","display_name":"Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7156137445","doi":"https://doi.org/10.48550/arxiv.2604.22031"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22031","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.22031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134717882","display_name":"Jo\u00e3o Mattos","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mattos, Jo\u00e3o","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134716812","display_name":"Arlei Silva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silva, Arlei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5134717882"],"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":0.987500011920929,"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":0.987500011920929,"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":0.0027000000700354576,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/unification","display_name":"Unification","score":0.7935000061988831},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7163000106811523},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6172000169754028},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.3720000088214874},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.34299999475479126},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.3174000084400177}],"concepts":[{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.7935000061988831},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7163000106811523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7001000046730042},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6172000169754028},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5145999789237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4058000147342682},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32679998874664307},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2727999985218048}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22031","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.22031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22031","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,52,103],"propose":[1],"Mochi,":[2,106],"a":[3,16,44,99],"Graph":[4,122],"Foundation":[5,123],"Model":[6],"that":[7,33,59,68,83,105],"addresses":[8],"task":[9,72],"unification":[10,46,101],"and":[11,31,56,64,135],"training":[12,19,91,143],"efficiency":[13],"by":[14],"adopting":[15],"meta-learning":[17],"based":[18],"framework.":[20],"Prior":[21],"models":[22],"pre-train":[23],"with":[24,40,93,108],"reconstruction-based":[25],"objectives":[26],"such":[27,48],"as":[28,49],"link":[29,133],"prediction,":[30,134],"assume":[32],"the":[34,85,90,146],"resulting":[35],"representations":[36],"can":[37],"be":[38],"aligned":[39],"downstream":[41,71,86],"tasks":[42],"through":[43,54],"separate":[45],"step":[47],"class":[50],"prototypes.":[51],"demonstrate":[53],"synthetic":[55],"real-world":[57,127],"experiments":[58],"this":[60],"procedure,":[61],"while":[62,138],"simple":[63],"intuitive,":[65],"has":[66],"limitations":[67],"directly":[69],"affect":[70],"performance.":[73],"To":[74],"address":[75],"these":[76],"limitations,":[77],"Mochi":[78],"pre-trains":[79],"on":[80,98],"few-shot":[81],"episodes":[82],"mirror":[84],"evaluation":[87],"protocol,":[88],"aligning":[89],"objective":[92],"inference":[94],"rather":[95],"than":[96,145],"relying":[97],"post-hoc":[100],"step.":[102],"show":[104],"along":[107],"its":[109],"more":[110],"powerful":[111],"variant":[112],"Mochi++,":[113],"achieves":[114],"competitive":[115],"or":[116],"superior":[117],"performance":[118],"compared":[119],"to":[120],"existing":[121],"Models":[124],"across":[125],"25":[126],"graph":[128,136],"datasets":[129],"spanning":[130],"node":[131],"classification,":[132,137],"requiring":[139],"8$\\sim$27":[140],"times":[141],"less":[142],"time":[144],"strongest":[147],"baseline.":[148]},"counts_by_year":[],"updated_date":"2026-04-28T06:12:00.211691","created_date":"2026-04-28T00:00:00"}
