{"id":"https://openalex.org/W7161709177","doi":"https://doi.org/10.48550/arxiv.2605.16902","title":"ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery","display_name":"ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161709177","doi":"https://doi.org/10.48550/arxiv.2605.16902"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.16902","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16902","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.16902","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136466849","display_name":"Haofei Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Haofei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136473118","display_name":"Jiaxuan You","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You, Jiaxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049837138","display_name":"Peter Clark","orcid":"https://orcid.org/0000-0003-1001-9226"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Clark, Peter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136486592","display_name":"Bodhisattwa Prasad Majumder","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Majumder, Bodhisattwa Prasad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136502110","display_name":"Kyle Richardson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Richardson, Kyle","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":0.5662000179290771,"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":0.5662000179290771,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.16660000383853912,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.10180000215768814,"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/ranking","display_name":"Ranking (information retrieval)","score":0.5024999976158142},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49059998989105225},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48559999465942383},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.462799996137619},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43810001015663147},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.4147000014781952},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4047999978065491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8145999908447266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5306000113487244},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5024999976158142},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49059998989105225},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48559999465942383},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4562000036239624},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4357999861240387},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.4147000014781952},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2858999967575073},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.16902","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16902","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.16902","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.16902","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Scientific":[0],"artifacts":[1,118,137],"such":[2],"as":[3,56,63],"models":[4],"and":[5,71,98,119,147,156],"datasets":[6],"are":[7,69,138],"foundations":[8],"for":[9,43,140],"research.":[10],"With":[11],"the":[12,39,124],"rapid":[13],"growth":[14],"of":[15,27,126],"platforms":[16],"like":[17],"HuggingFace,":[18],"researchers":[19],"now":[20],"have":[21],"access":[22],"to":[23,122],"a":[24,30,44,78,112],"large":[25],"number":[26],"artifacts.":[28],"Yet,":[29],"key":[31],"challenge":[32],"remains:":[33],"how":[34],"can":[35],"we":[36],"automatically":[37],"discover":[38,152],"state-of-the-art":[40],"(SOTA)":[41],"model":[42],"given":[45],"dataset":[46],"by":[47,60],"fully":[48],"leveraging":[49],"existing":[50,136],"artifacts?":[51],"We":[52,75,109],"formalize":[53],"this":[54],"task":[55],"automatic":[57],"SOTA":[58,154],"discovery":[59],"modeling":[61],"HuggingFace":[62],"an":[64],"artifact":[65],"graph,":[66],"where":[67],"nodes":[68],"models/datasets":[70],"edges":[72],"represent":[73],"evaluations.":[74],"propose":[76],"ArtifactLinker,":[77],"two-stage":[79],"framework:":[80],"(1)":[81,132],"ranking":[82,146],"promising":[83],"unobserved":[84],"model--dataset":[85],"links":[86,102],"using":[87],"Graph":[88],"Neural":[89],"Networks":[90],"(GNNs)":[91],"or":[92],"graph-augmented":[93],"Large":[94],"Language":[95],"Models":[96],"(LLMs),":[97],"(2)":[99,144],"verifying":[100],"top-ranked":[101],"via":[103],"coding":[104],"experiments":[105],"with":[106,116,149],"LLM-based":[107],"agents.":[108],"further":[110],"introduce":[111],"benchmark":[113],"named":[114],"ArtifactBench":[115],"14,053":[117],"51,337":[120],"relations":[121],"evaluate":[123],"performance":[125],"both":[127],"stages.":[128],"Results":[129],"show":[130],"that":[131],"graph":[133],"structures":[134],"between":[135],"effective":[139],"missing":[141],"link":[142],"prediction;":[143],"end-to-end":[145],"verification":[148],"ArtifactLinker":[150],"help":[151],"potential":[153],"results":[155],"research":[157],"insights.":[158]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-20T00:00:00"}