{"id":"https://openalex.org/W4406458658","doi":"https://doi.org/10.1109/bigdata62323.2024.10825667","title":"Generating Descriptive Explanations of Machine Learning Models Using LLM","display_name":"Generating Descriptive Explanations of Machine Learning Models Using LLM","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458658","doi":"https://doi.org/10.1109/bigdata62323.2024.10825667"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/38c22fd9-1a02-488d-841c-82d25e7663bd/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045684529","display_name":"Anqi Pang","orcid":"https://orcid.org/0000-0003-2746-6946"},"institutions":[{"id":"https://openalex.org/I4210132851","display_name":"Horace Mann School","ror":"https://ror.org/040yys981","country_code":"US","type":"education","lineage":["https://openalex.org/I4210132851"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Pang","raw_affiliation_strings":["Horace Greeley High School,NY"],"affiliations":[{"raw_affiliation_string":"Horace Greeley High School,NY","institution_ids":["https://openalex.org/I4210132851"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046714396","display_name":"Hyeju Jang","orcid":"https://orcid.org/0000-0002-7652-1158"},"institutions":[{"id":"https://openalex.org/I4388446366","display_name":"Indiana University Indianapolis","ror":"https://ror.org/03eftgw80","country_code":null,"type":"education","lineage":["https://openalex.org/I4388446366","https://openalex.org/I592451"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyeju Jang","raw_affiliation_strings":["Indiana University Indianapolis,Luddy School of Informatics, Computing and Engineering"],"affiliations":[{"raw_affiliation_string":"Indiana University Indianapolis,Luddy School of Informatics, Computing and Engineering","institution_ids":["https://openalex.org/I55769427","https://openalex.org/I4388446366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004575115","display_name":"Shiaofen Fang","orcid":"https://orcid.org/0000-0001-8277-5202"},"institutions":[{"id":"https://openalex.org/I4388446366","display_name":"Indiana University Indianapolis","ror":"https://ror.org/03eftgw80","country_code":null,"type":"education","lineage":["https://openalex.org/I4388446366","https://openalex.org/I592451"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiaofen Fang","raw_affiliation_strings":["Indiana University Indianapolis,Luddy School of Informatics, Computing and Engineering"],"affiliations":[{"raw_affiliation_string":"Indiana University Indianapolis,Luddy School of Informatics, Computing and Engineering","institution_ids":["https://openalex.org/I55769427","https://openalex.org/I4388446366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045684529"],"corresponding_institution_ids":["https://openalex.org/I4210132851"],"apc_list":null,"apc_paid":null,"fwci":1.4176,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85691118,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5369","last_page":"5374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9986000061035156,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9986000061035156,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9796000123023987,"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/computer-science","display_name":"Computer science","score":0.7043049335479736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49235379695892334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45890137553215027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7043049335479736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49235379695892334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45890137553215027}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarworks.indianapolis.iu.edu:1805/54420","is_oa":true,"landing_page_url":"https://hdl.handle.net/1805/54420","pdf_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/38c22fd9-1a02-488d-841c-82d25e7663bd/download","source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:scholarworks.indianapolis.iu.edu:1805/54420","is_oa":true,"landing_page_url":"https://hdl.handle.net/1805/54420","pdf_url":"https://scholarworks.indianapolis.iu.edu/bitstreams/38c22fd9-1a02-488d-841c-82d25e7663bd/download","source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Author","raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406458658.pdf","grobid_xml":"https://content.openalex.org/works/W4406458658.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1501005121","https://openalex.org/W1980276779","https://openalex.org/W2013293739","https://openalex.org/W2045649112","https://openalex.org/W2147169375","https://openalex.org/W2223235514","https://openalex.org/W2332488709","https://openalex.org/W2343061342","https://openalex.org/W2516809705","https://openalex.org/W2613099550","https://openalex.org/W2795530988","https://openalex.org/W2824228311","https://openalex.org/W2886614482","https://openalex.org/W2891503716","https://openalex.org/W2902809094","https://openalex.org/W2913994026","https://openalex.org/W2939803556","https://openalex.org/W2945807221","https://openalex.org/W2954503794","https://openalex.org/W2973142595","https://openalex.org/W2979845414","https://openalex.org/W2999134777","https://openalex.org/W3000840260","https://openalex.org/W3011179515","https://openalex.org/W3044826997","https://openalex.org/W3105396370","https://openalex.org/W3124516888","https://openalex.org/W3212246833","https://openalex.org/W4285340650","https://openalex.org/W4292289324","https://openalex.org/W4299847293","https://openalex.org/W4307212054","https://openalex.org/W6638389677","https://openalex.org/W6733905848","https://openalex.org/W6751916690","https://openalex.org/W6780941489","https://openalex.org/W6798796605"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Machine":[0],"learning":[1,24,43,66],"algorithms":[2],"play":[3],"a":[4,8,22,28,35,46,64,69,91,137,142],"pivotal":[5],"role":[6],"in":[7,90],"wide":[9],"range":[10],"of":[11,21,41,59,63,71,118],"Artificial":[12],"Intelligence":[13],"(AI)":[14],"applications.":[15],"Explaining":[16],"the":[17,39,60,103,124],"results":[18],"and":[19,73,110,129,141],"behavior":[20],"machine":[23,42,65],"model,":[25],"however,":[26],"remains":[27],"challenge.":[29],"In":[30,51],"this":[31,52],"paper,":[32],"we":[33,54],"present":[34],"new":[36],"approach":[37,150],"to":[38,82,101,123,126,147],"explanation":[40],"models":[44],"using":[45,87],"large":[47],"language":[48,57,132],"model":[49,67,74,85],"(LLM).":[50],"work,":[53],"seek":[55],"natural":[56,131],"descriptions":[58],"behavioral":[61],"patterns":[62],"by":[68],"combination":[70],"prompting":[72],"sampling.":[75],"A":[76,95],"subspace":[77],"sampling":[78,104,109],"technique":[79],"is":[80,99],"developed":[81],"generate":[83],"ML":[84],"outputs":[86],"partial":[88],"features":[89],"user":[92],"defined":[93],"space.":[94],"projective":[96],"visualization":[97],"method":[98],"employed":[100],"guide":[102],"process,":[105],"including":[106],"user-directed":[107],"interactive":[108],"feature-based":[111],"sampling,":[112],"so":[113],"that":[114],"an":[115],"optimal":[116],"amount":[117],"information":[119],"can":[120],"be":[121],"provided":[122],"LLM":[125],"ensure":[127],"accurate":[128],"concise":[130],"explanations.":[133],"Two":[134],"public":[135],"datasets,":[136],"student":[138],"performance":[139],"dataset":[140],"weather":[143],"dataset,":[144],"were":[145],"used":[146],"test":[148],"our":[149],"under":[151],"various":[152],"conditions.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}