{"id":"https://openalex.org/W7164502235","doi":"https://doi.org/10.48550/arxiv.2606.13020","title":"SciR: A Controllable Benchmark for Scientific Reasoning in LLMs","display_name":"SciR: A Controllable Benchmark for Scientific Reasoning in LLMs","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164502235","doi":"https://doi.org/10.48550/arxiv.2606.13020"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13020","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.2606.13020","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134136962","display_name":"Pierre Beckmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Beckmann, Pierre","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138486907","display_name":"Marco Valentino","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valentino, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138544870","display_name":"Andre Freitas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Freitas, Andre","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/T10028","display_name":"Topic Modeling","score":0.5202000141143799,"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/T10028","display_name":"Topic Modeling","score":0.5202000141143799,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.11140000075101852,"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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.10270000249147415,"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/inference","display_name":"Inference","score":0.8040000200271606},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6352999806404114},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5666999816894531},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.48330000042915344},{"id":"https://openalex.org/keywords/scientific-modelling","display_name":"Scientific modelling","score":0.4311000108718872},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40860000252723694},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.3903999924659729},{"id":"https://openalex.org/keywords/inductive-reasoning","display_name":"Inductive reasoning","score":0.3515999913215637}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.8040000200271606},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6352999806404114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6290000081062317},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4796000123023987},{"id":"https://openalex.org/C138379479","wikidata":"https://www.wikidata.org/wiki/Q1116876","display_name":"Scientific modelling","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3625999987125397},{"id":"https://openalex.org/C21563000","wikidata":"https://www.wikidata.org/wiki/Q484511","display_name":"Inductive reasoning","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C2992562121","wikidata":"https://www.wikidata.org/wiki/Q3817808","display_name":"Scientific reasoning","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.32359999418258667},{"id":"https://openalex.org/C3746660","wikidata":"https://www.wikidata.org/wiki/Q1068763","display_name":"Rule of inference","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.2985999882221222},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C195732255","wikidata":"https://www.wikidata.org/wiki/Q981008","display_name":"Sociology of scientific knowledge","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C166088908","wikidata":"https://www.wikidata.org/wiki/Q308495","display_name":"Abductive reasoning","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13020","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.2606.13020","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13020","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.47637590765953064}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Three":[0],"paradigmatic":[1,66],"forms":[2],"of":[3,25],"inference":[4,122,146,172,191],"recur":[5],"across":[6],"scientific":[7,20,27,48,61,67,90],"reasoning:":[8],"deduction,":[9],"induction,":[10],"and":[11,35,117,134,190],"causal":[12,80],"abduction.":[13],"Reliably":[14],"evaluating":[15],"LLMs":[16],"on":[17,30,64,170,187],"these":[18],"in":[19],"settings":[21],"is":[22,108,178],"currently":[23],"out":[24],"reach:":[26],"benchmarks":[28,43],"built":[29],"human":[31],"annotations":[32],"are":[33,70],"costly":[34],"lack":[36],"mechanistic":[37],"ground":[38],"truth,":[39],"while":[40],"synthetic":[41],"logical-reasoning":[42],"do":[44],"not":[45],"resemble":[46],"real":[47],"documents.":[49],"We":[50,125],"introduce":[51],"SciR,":[52],"a":[53,148,155],"benchmark":[54,183],"that":[55],"combines":[56],"multi-paradigm":[57,181],"reasoning":[58,161],"with":[59,184],"controllable":[60],"rendering,":[62],"anchored":[63],"three":[65],"problems.":[68],"Tasks":[69],"generated":[71],"from":[72],"formal":[73],"objects":[74],"(deduction":[75],"tree,":[76],"inductive":[77],"rule":[78],"hypothesis,":[79],"graph)":[81],"to":[82,109,147],"guarantee":[83],"verifiable":[84],"answers,":[85],"then":[86],"rendered":[87],"into":[88],"multi-document":[89],"discourse":[91],"via":[92],"per-track":[93],"domain-tuned":[94],"genres.":[95],"The":[96,138,151],"construction":[97],"lets":[98],"us":[99],"independently":[100],"vary":[101],"two":[102,152],"difficulty":[103],"axes:":[104],"how":[105,118],"hard":[106,119],"it":[107],"extract":[110],"the":[111,120,171,179],"key":[112],"information":[113],"needed":[114],"for":[115,159],"inference,":[116],"principled":[121],"itself":[123],"is.":[124],"test":[126],"six":[127],"models.":[128],"Both":[129],"axes":[130,153],"hurt":[131],"every":[132],"model,":[133],"their":[135],"effects":[136],"compound.":[137],"rendering":[139],"even":[140],"hurts":[141],"neurosymbolic":[142],"pipelines,":[143],"which":[144],"hand":[145],"verified":[149],"solver.":[150],"yield":[154],"per-model":[156],"extraction-vs-inference":[157],"profile:":[158],"instance,":[160],"models":[162,169],"like":[163],"deepseek-r1":[164],"mostly":[165],"surpass":[166],"non-reasoning":[167],"instruct":[168],"axis.":[173],"To":[174],"our":[175],"knowledge,":[176],"SciR":[177],"first":[180],"scientific-reasoning":[182],"parametric":[185],"control":[186],"both":[188],"extraction":[189],"difficulty.":[192]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-13T00:00:00"}