{"id":"https://openalex.org/W7155071148","doi":"https://doi.org/10.48550/arxiv.2604.17141","title":"SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction","display_name":"SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction","publication_year":2026,"publication_date":"2026-04-18","ids":{"openalex":"https://openalex.org/W7155071148","doi":"https://doi.org/10.48550/arxiv.2604.17141"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17141","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17141","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.2604.17141","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101604041","display_name":"Hangxiao Zhu","orcid":"https://orcid.org/0009-0007-1394-3410"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Hangxiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134168095","display_name":"Yuyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yuyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134192007","display_name":"Ping Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065251926","display_name":"Zhang Yu","orcid":"https://orcid.org/0000-0002-2567-5851"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yu","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/T10102","display_name":"scientometrics and bibliometrics research","score":0.41179999709129333,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10102","display_name":"scientometrics and bibliometrics research","score":0.41179999709129333,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.1647000014781952,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11937","display_name":"Research Data Management Practices","score":0.09070000052452087,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8574000000953674},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.49399998784065247},{"id":"https://openalex.org/keywords/citation","display_name":"Citation","score":0.45260000228881836},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.40459999442100525},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.3675999939441681},{"id":"https://openalex.org/keywords/silver-bullet","display_name":"Silver bullet","score":0.3467999994754791},{"id":"https://openalex.org/keywords/scientific-literature","display_name":"Scientific literature","score":0.32499998807907104}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8574000000953674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6294000148773193},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5893999934196472},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.49399998784065247},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4072999954223633},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.366100013256073},{"id":"https://openalex.org/C2776088982","wikidata":"https://www.wikidata.org/wiki/Q841402","display_name":"Silver bullet","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3425999879837036},{"id":"https://openalex.org/C2781083858","wikidata":"https://www.wikidata.org/wiki/Q17327049","display_name":"Scientific literature","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C111874474","wikidata":"https://www.wikidata.org/wiki/Q6005872","display_name":"Impact assessment","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.30399999022483826},{"id":"https://openalex.org/C138379479","wikidata":"https://www.wikidata.org/wiki/Q1116876","display_name":"Scientific modelling","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2806999981403351},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2799000144004822},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C184356942","wikidata":"https://www.wikidata.org/wiki/Q830382","display_name":"Best practice","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C2778407487","wikidata":"https://www.wikidata.org/wiki/Q14565201","display_name":"Altmetrics","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C178315738","wikidata":"https://www.wikidata.org/wiki/Q603441","display_name":"Bibliometrics","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17141","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17141","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.2604.17141","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17141","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":{"The":[0],"rapid":[1],"growth":[2],"of":[3,27,57],"scientific":[4,47,58,169],"literature":[5],"calls":[6],"for":[7,46,166],"automated":[8],"methods":[9],"to":[10,30,64,139],"assess":[11],"and":[12,71,79,100,127,147,162],"predict":[13],"research":[14],"impact.":[15],"Prior":[16],"work":[17],"has":[18],"largely":[19],"focused":[20],"on":[21,115],"citation-based":[22],"metrics,":[23],"leaving":[24],"limited":[25],"evaluation":[26],"models'":[28],"capability":[29],"reason":[31],"about":[32],"other":[33],"impact":[34,48,91,170],"dimensions.":[35],"To":[36],"this":[37],"end,":[38],"we":[39],"introduce":[40],"SciImpact,":[41],"a":[42,159],"large-scale,":[43],"multi-dimensional":[44],"benchmark":[45,161],"prediction":[49],"spanning":[50],"19":[51],"fields.":[52],"SciImpact":[53,157],"captures":[54],"various":[55],"forms":[56],"influence,":[59],"ranging":[60],"from":[61],"citation":[62],"counts":[63],"award":[65],"recognition,":[66],"media":[67],"attention,":[68],"patent":[69],"reference,":[70],"artifact":[72],"adoption,":[73],"by":[74],"integrating":[75],"heterogeneous":[76],"data":[77],"sources":[78],"targeted":[80],"web":[81],"crawling.":[82],"It":[83],"comprises":[84],"215,928":[85],"contrastive":[86],"paper":[87],"pairs":[88],"reflecting":[89],"meaningful":[90],"differences":[92],"in":[93],"both":[94],"short-term":[95],"(e.g.,":[96,103,137,145,152],"Best":[97],"Paper":[98],"Award)":[99],"long-term":[101],"settings":[102],"Nobel":[104],"Prize).":[105],"We":[106],"evaluate":[107],"11":[108],"widely":[109],"used":[110],"large":[111],"language":[112],"models":[113,121,144],"(LLMs)":[114],"SciImpact.":[116],"Results":[117],"show":[118],"that":[119],"off-the-shelf":[120],"exhibit":[122],"substantial":[123],"variability":[124],"across":[125],"dimensions":[126],"fields,":[128],"while":[129],"multi-task":[130],"supervised":[131],"fine-tuning":[132],"consistently":[133],"enables":[134],"smaller":[135],"LLMs":[136,151],"4B)":[138],"markedly":[140],"outperform":[141],"much":[142],"larger":[143],"30B)":[146],"surpass":[148],"powerful":[149],"closed-source":[150],"o4-mini).":[153],"These":[154],"results":[155],"establish":[156],"as":[158],"challenging":[160],"demonstrate":[163],"its":[164],"value":[165],"multi-dimensional,":[167],"multi-field":[168],"prediction.":[171],"Our":[172],"project":[173],"homepage":[174],"is":[175],"https://flypig23.github.io/sciimpact-homepage/":[176]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}
