{"id":"https://openalex.org/W7160592574","doi":"https://doi.org/10.48550/arxiv.2605.05758","title":"BioTool: A Comprehensive Tool-Calling Dataset for Enhancing Biomedical Capabilities of Large Language Models","display_name":"BioTool: A Comprehensive Tool-Calling Dataset for Enhancing Biomedical Capabilities of Large Language Models","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160592574","doi":"https://doi.org/10.48550/arxiv.2605.05758"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05758","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05758","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":"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.2605.05758","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135641222","display_name":"Xin Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135652205","display_name":"Ruiyi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ruiyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135651392","display_name":"Meixi Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Meixi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135720292","display_name":"Peijia Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Peijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135648789","display_name":"Pengtao Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Pengtao","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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6521999835968018,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.6521999835968018,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.0746999979019165,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.07280000299215317,"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/biomedicine","display_name":"Biomedicine","score":0.7615000009536743},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6819000244140625},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5159000158309937},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46470001339912415},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.40139999985694885},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.38420000672340393}],"concepts":[{"id":"https://openalex.org/C66782513","wikidata":"https://www.wikidata.org/wiki/Q864601","display_name":"Biomedicine","level":2,"score":0.7615000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049999833106995},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6819000244140625},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5159000158309937},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4805000126361847},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.38420000672340393},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3230000138282776},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3057999908924103},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.257999986410141},{"id":"https://openalex.org/C135257023","wikidata":"https://www.wikidata.org/wiki/Q691358","display_name":"Domain-specific language","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05758","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05758","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":"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.2605.05758","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05758","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":"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,26,55,63,104,164,171,177],"success":[2],"of":[3,28,57,78,173,180],"large":[4],"language":[5],"models":[6,73],"(LLMs)":[7],"on":[8,42,68,130],"general-purpose":[9],"tasks,":[10],"their":[11],"performance":[12],"in":[13,44,62,135,175],"highly":[14],"specialized":[15],"domains":[16],"such":[17,143],"as":[18,144],"biomedicine":[19],"remains":[20],"unsatisfactory.":[21],"A":[22],"key":[23],"limitation":[24],"is":[25],"inability":[27],"LLMs":[29,142],"to":[30,74,163],"effectively":[31],"leverage":[32],"biomedical":[33,39,64,89,136,178],"tools,":[34],"which":[35],"clinical":[36],"experts":[37],"and":[38,71,107,123,185],"researchers":[40],"rely":[41,67],"extensively":[43],"daily":[45],"workflows.":[46],"While":[47],"recent":[48],"general-domain":[49],"tool-calling":[50,90,137],"datasets":[51],"have":[52],"substantially":[53],"improved":[54],"capabilities":[56,179],"LLM":[58,129,166],"agents,":[59],"existing":[60],"efforts":[61],"domain":[65],"largely":[66],"in-context":[69],"learning":[70],"restrict":[72],"a":[75,87,127,153],"small":[76],"set":[77],"tools.":[79],"To":[80],"address":[81],"this":[82],"gap,":[83],"we":[84],"introduce":[85],"BioTool,":[86],"comprehensive":[88],"dataset":[91,184],"designed":[92],"for":[93],"fine-tuning":[94],"LLMs.":[95,181],"BioTool":[96,131,174],"comprises":[97],"34":[98],"frequently":[99],"used":[100],"tools":[101],"collected":[102],"from":[103],"NCBI,":[105],"Ensembl,":[106],"UniProt":[108],"databases,":[109],"along":[110],"with":[111],"7,040":[112],"high-quality,":[113],"human-verified":[114],"query-API":[115],"call":[116],"pairs":[117],"spanning":[118],"variation,":[119],"genomics,":[120],"proteomics,":[121],"evolution,":[122],"general":[124],"biology.":[125],"Fine-tuning":[126],"4-billion-parameter":[128],"yields":[132],"substantial":[133],"improvements":[134],"performance,":[138],"outperforming":[139],"cutting-edge":[140],"commercial":[141],"GPT-5.1.":[145],"Furthermore,":[146],"human":[147],"expert":[148],"evaluations":[149],"demonstrate":[150],"that":[151],"integrating":[152],"BioTool-fine-tuned":[154],"tool":[155,168],"caller":[156],"significantly":[157],"improves":[158],"downstream":[159],"answer":[160],"quality":[161],"compared":[162],"same":[165],"without":[167],"usage,":[169],"highlighting":[170],"effectiveness":[172],"enhancing":[176],"The":[182],"full":[183],"evaluation":[186],"code":[187],"are":[188],"available":[189],"at":[190],"https://github.com/gxx27/BioTool":[191]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}
