{"id":"https://openalex.org/W7130549663","doi":"https://doi.org/10.48550/arxiv.2602.16653","title":"Agent Skill Framework: Perspectives on the Potential of Small Language Models in Industrial Environments","display_name":"Agent Skill Framework: Perspectives on the Potential of Small Language Models in Industrial Environments","publication_year":2026,"publication_date":"2026-02-18","ids":{"openalex":"https://openalex.org/W7130549663","doi":"https://doi.org/10.48550/arxiv.2602.16653"},"language":null,"primary_location":{"id":"pmh:oai:zenodo.org:18868295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arXiv.2602.16653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arXiv.2602.16653","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126370893","display_name":"Yangjie Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xu, Yangjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121717763","display_name":"Lujun Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Lujun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126364404","display_name":"Lama Sleem","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sleem, Lama","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012553801","display_name":"Niccol\u00f2 Gentile","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gentile, Niccolo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126370446","display_name":"Yewei Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yewei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126383832","display_name":"Yiqun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yiqun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126406842","display_name":"Siming Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Siming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126404806","display_name":"Wenbo Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Wenbo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5069228908","display_name":"Radu State","orcid":"https://orcid.org/0000-0002-4751-9577"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"State, Radu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5126370893"],"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/T14347","display_name":"Big Data and Digital Economy","score":0.17599999904632568,"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"}},"topics":[{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.17599999904632568,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.12770000100135803,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.07370000332593918,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/task","display_name":"Task (project management)","score":0.5697000026702881},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5386000275611877},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5335000157356262},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.44519999623298645},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4300000071525574},{"id":"https://openalex.org/keywords/budget-constraint","display_name":"Budget constraint","score":0.42649999260902405}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7143999934196472},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5697000026702881},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5386000275611877},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5335000157356262},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4050999879837036},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3637000024318695},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3495999872684479},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.34689998626708984},{"id":"https://openalex.org/C2780873155","wikidata":"https://www.wikidata.org/wiki/Q392811","display_name":"Agent-based model","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3034999966621399},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2985000014305115},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29580000042915344},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2827000021934509},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:zenodo.org:18868295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arXiv.2602.16653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/preprint"},{"id":"doi:10.48550/arxiv.2602.16653","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.16653","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:oai:zenodo.org:18868295","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arXiv.2602.16653","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/preprint"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5368191003799438,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Agent":[0,46,98,153,199],"Skill":[1,47,99,154],"framework,":[2,189],"now":[3],"widely":[4],"and":[5,16,30,74,78,122,179,185],"officially":[6],"supported":[7],"by":[8,24,102],"major":[9],"players":[10],"such":[11],"as":[12],"GitHub":[13],"Copilot,":[14],"LangChain,":[15],"OpenAI,":[17],"performs":[18],"especially":[19],"well":[20],"with":[21,136],"proprietary":[22],"models":[23,55,108,134],"improving":[25,170],"context":[26],"engineering,":[27],"reducing":[28],"hallucinations,":[29],"boosting":[31],"task":[32],"accuracy.":[33],"Based":[34],"on":[35,66],"these":[36,174],"observations,":[37],"an":[38],"investigation":[39],"is":[40,69],"conducted":[41],"to":[42,52,72,166],"determine":[43],"whether":[44],"the":[45,97,152,183,188,195],"paradigm":[48],"provides":[49],"similar":[50],"benefits":[51],"small":[53],"language":[54,107],"(SLMs).":[56],"This":[57,89],"question":[58],"matters":[59],"in":[60,85,201],"industrial":[61],"scenarios":[62],"where":[63,79],"continuous":[64],"reliance":[65],"public":[67],"APIs":[68],"infeasible":[70],"due":[71],"data-security":[73],"budget":[75],"constraints":[76,186],"requirements,":[77],"SLMs":[80,143],"often":[81],"show":[82,131],"limited":[83],"generalization":[84],"highly":[86],"customized":[87],"scenarios.":[88],"work":[90],"introduces":[91],"a":[92,103,123,177],"formal":[93],"mathematical":[94],"definition":[95],"of":[96,106,109,182,187,198],"process,":[100],"followed":[101],"systematic":[104],"evaluation":[105,117],"varying":[110],"sizes":[111],"across":[112],"multiple":[113],"use":[114],"cases.":[115],"The":[116,129],"encompasses":[118],"two":[119],"open-source":[120],"tasks":[121],"real-world":[124],"insurance":[125],"claims":[126],"data":[127],"set.":[128],"results":[130],"that":[132],"tiny":[133],"struggle":[135],"reliable":[137],"skill":[138],"selection,":[139],"while":[140,169,190],"moderately":[141],"sized":[142],"(approximately":[144],"12B":[145],"-":[146],"30B)":[147],"parameters)":[148],"benefit":[149],"substantially":[150],"from":[151],"approach.":[155],"Moreover,":[156],"code-specialized":[157],"variants":[158],"at":[159],"around":[160],"80B":[161],"parameters":[162],"achieve":[163],"performance":[164],"comparable":[165],"closed-source":[167],"baselines":[168],"GPU":[171],"efficiency.":[172],"Collectively,":[173],"findings":[175],"provide":[176],"comprehensive":[178],"nuanced":[180],"characterization":[181],"capabilities":[184],"providing":[191],"actionable":[192],"insights":[193],"for":[194],"effective":[196],"deployment":[197],"Skills":[200],"SLM-centered":[202],"environments.":[203]},"counts_by_year":[],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2026-02-20T00:00:00"}