{"id":"https://openalex.org/W7148426121","doi":"https://doi.org/10.48550/arxiv.2604.00554","title":"LLM-supported document separation for printed reviews from zbMATH Open","display_name":"LLM-supported document separation for printed reviews from zbMATH Open","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148426121","doi":"https://doi.org/10.48550/arxiv.2604.00554"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.00554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00554","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.2604.00554","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132745688","display_name":"Ivan Pluzhnikov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pluzhnikov, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000746968","display_name":"Ankit Satpute","orcid":"https://orcid.org/0000-0003-3219-026X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satpute, Ankit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038664667","display_name":"Moritz Schubotz","orcid":"https://orcid.org/0000-0001-7141-4997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schubotz, Moritz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015124068","display_name":"Olaf Teschke","orcid":"https://orcid.org/0009-0003-4089-9647"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teschke, Olaf","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058837356","display_name":"B\u00e9la Gipp","orcid":"https://orcid.org/0000-0001-6522-3019"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gipp, Bela","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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.7630000114440918,"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":0.7630000114440918,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.20559999346733093,"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/T12170","display_name":"History and Theory of Mathematics","score":0.003100000089034438,"subfield":{"id":"https://openalex.org/subfields/2614","display_name":"Theoretical Computer Science"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7598999738693237},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.5717999935150146},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5439000129699707},{"id":"https://openalex.org/keywords/document-processing","display_name":"Document processing","score":0.436599999666214},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.4221000075340271},{"id":"https://openalex.org/keywords/document-retrieval","display_name":"Document retrieval","score":0.383899986743927},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.37380000948905945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8651000261306763},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7598999738693237},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5853000283241272},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.5717999935150146},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5439000129699707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5235999822616577},{"id":"https://openalex.org/C67905146","wikidata":"https://www.wikidata.org/wiki/Q5287646","display_name":"Document processing","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3970000147819519},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.383899986743927},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C2777737414","wikidata":"https://www.wikidata.org/wiki/Q4868296","display_name":"Font","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C68699486","wikidata":"https://www.wikidata.org/wiki/Q265904","display_name":"Document Structure Description","level":3,"score":0.3165999948978424},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.30799999833106995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28859999775886536},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.2824000120162964},{"id":"https://openalex.org/C2779500292","wikidata":"https://www.wikidata.org/wiki/Q14802672","display_name":"Text processing","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.00554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00554","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.2604.00554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00554","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":[{"score":0.5812823176383972,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,172],"paper":[1],"presents":[2],"a":[3,15,124,186],"specialized":[4],"methodology":[5],"for":[6,60,97,147,202,213],"digitizing":[7],"and":[8,53,75,106,120,144,181,197,221],"segmenting":[9],"mathematical":[10,19,192,214],"documents":[11,29,52,193,204],"from":[12],"zbMATH":[13],"Open,":[14],"comprehensive":[16],"database":[17],"of":[18,135,149,156,166],"literature,":[20],"to":[21],"enhance":[22],"machine":[23,218],"processing":[24],"capabilities.":[25],"Currently,":[26],"approximately":[27],"831,000":[28],"exist":[30],"only":[31],"in":[32,162,205],"scanned":[33],"volumes,":[34],"which":[35],"makes":[36],"them":[37,122],"not":[38],"machine-processable.":[39],"Furthermore,":[40],"these":[41,65],"scans":[42],"often":[43],"span":[44],"multiple":[45],"pages":[46,49],"or":[47],"share":[48],"with":[50,153],"other":[51],"incorporate":[54],"diverse":[55],"typesetting":[56],"techniques,":[57,78],"posing":[58],"challenges":[59],"automated":[61],"processing.":[62],"To":[63],"address":[64],"issues,":[66],"we":[67,113,189],"evaluate":[68],"various":[69],"Optical":[70],"Character":[71],"Recognition":[72],"(OCR)":[73],"tools":[74],"document":[76,111,200],"separation":[77],"proposing":[79],"an":[80,154,163],"optimized":[81],"pipeline":[82],"that":[83],"outperforms":[84],"existing":[85],"approaches.":[86],"Our":[87],"study":[88],"identifies":[89,141],"Mathpix":[90],"as":[91],"the":[92,133,136,142,150,169],"most":[93],"effective":[94],"OCR":[95],"tool":[96],"LaTeX":[98,206],"conversion,":[99],"demonstrating":[100],"superior":[101],"performance":[102],"based":[103],"on":[104,158,168],"BLEU":[105],"Edit":[107],"Distance":[108],"metrics.":[109],"For":[110],"separation,":[112],"fine-tune":[114],"generative":[115],"Large":[116],"Language":[117],"Models":[118],"(LLMs)":[119],"integrate":[121],"into":[123,194],"Majority":[125],"Voting":[126],"framework,":[127],"achieving":[128],"97.5%":[129],"accuracy":[130,155,165],"when":[131],"providing":[132],"text":[134,196],"document.":[137],"Additionally,":[138],"our":[139],"method":[140],"start":[143],"end":[145],"indexes":[146],"90.6%":[148],"test":[151],"dataset,":[152],"98.4%":[157],"applicable":[159],"cases,":[160],"resulting":[161],"overall":[164],"89.1%":[167],"entire":[170],"dataset.":[171],"approach":[173],"surpasses":[174],"traditional":[175],"baselines,":[176],"including":[177],"regular":[178],"expressions,":[179],"ChatGPT-4o,":[180],"computer":[182],"vision-based":[183],"techniques.":[184],"As":[185],"practical":[187],"outcome,":[188],"process":[190],"810,977":[191],"machine-readable":[195],"extract":[198],"precise":[199],"boundaries":[201],"721,288":[203],"format.":[207],"These":[208],"contributions":[209],"significantly":[210],"improve":[211],"accessibility":[212],"information":[215],"retrieval":[216],"systems,":[217],"learning":[219],"models,":[220],"related":[222],"applications.":[223]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-03T00:00:00"}
