{"id":"https://openalex.org/W7133220068","doi":"https://doi.org/10.48550/arxiv.2602.24173","title":"LemmaBench: A Live, Research-Level Benchmark to Evaluate LLM Capabilities in Mathematics","display_name":"LemmaBench: A Live, Research-Level Benchmark to Evaluate LLM Capabilities in Mathematics","publication_year":2026,"publication_date":"2026-02-27","ids":{"openalex":"https://openalex.org/W7133220068","doi":"https://doi.org/10.48550/arxiv.2602.24173"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.24173","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032420653","display_name":"Antoine Peyronnet","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Peyronnet, Antoine","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092698871","display_name":"Fabian Gloeckle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gloeckle, Fabian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5005034959","display_name":"Amaury Hayat","orcid":"https://orcid.org/0000-0002-7017-1097"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hayat, Amaury","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032420653"],"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.4399000108242035,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.4399000108242035,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.15230000019073486,"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":0.06599999964237213,"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/benchmark","display_name":"Benchmark (surveying)","score":0.9315000176429749},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8687000274658203},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6947000026702881},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6660000085830688},{"id":"https://openalex.org/keywords/contest","display_name":"CONTEST","score":0.5658000111579895}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.9315000176429749},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8687000274658203},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6947000026702881},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6660000085830688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6536999940872192},{"id":"https://openalex.org/C2777582232","wikidata":"https://www.wikidata.org/wiki/Q5013414","display_name":"CONTEST","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43309998512268066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41040000319480896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3555999994277954},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3452000021934509},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3407000005245209},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26010000705718994}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.24173","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.24173","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.24173","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":"pmh:doi:10.48550/arxiv.2602.24173","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7380782961845398,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,105],"present":[1],"a":[2,77,128,141],"new":[3,85],"approach":[4],"for":[5,30,99,133],"benchmarking":[6],"Large":[7],"Language":[8],"Model":[9],"(LLM)":[10],"capabilities":[11,139],"on":[12,19,42,120],"research-level":[13],"mathematics.":[14,48],"Existing":[15],"benchmarks":[16],"largely":[17],"rely":[18],"static,":[20],"hand-curated":[21],"sets":[22],"of":[23,51,131],"contest":[24],"or":[25],"textbook-style":[26],"problems":[27,86],"as":[28],"proxies":[29],"mathematical":[31,91],"research.":[32],"Instead,":[33],"we":[34],"establish":[35],"an":[36,52],"updatable":[37],"benchmark":[38,78,106],"evaluating":[39],"models":[40],"directly":[41,88],"the":[43,121],"latest":[44],"research":[45,142],"results":[46,75],"in":[47,76,115,140],"This":[49],"consists":[50],"automatic":[53],"pipeline":[54],"that":[55,79,124],"extracts":[56],"lemmas":[57],"from":[58,89],"arXiv":[59],"and":[60,70],"rewrites":[61],"them":[62],"into":[63],"self-contained":[64],"statements":[65],"by":[66],"making":[67],"all":[68],"assumptions":[69],"required":[71],"definitions":[72],"explicit.":[73],"It":[74],"can":[80,96],"be":[81,97],"updated":[82],"regularly":[83],"with":[84],"taken":[87],"human":[90],"research,":[92],"while":[93],"previous":[94],"instances":[95],"used":[98],"training":[100],"without":[101],"compromising":[102],"future":[103],"evaluations.":[104],"current":[107],"state-of-the-art":[108],"LLMs,":[109],"which":[110],"obtain":[111],"around":[112],"10-15$\\%$":[113],"accuracy":[114],"theorem":[116],"proving":[117,138],"(pass@1)":[118],"depending":[119],"model,":[122],"showing":[123],"there":[125],"is":[126],"currently":[127],"large":[129],"margin":[130],"progression":[132],"LLMs":[134],"to":[135],"reach":[136],"human-level":[137],"context.":[143]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-03-03T00:00:00"}
