{"id":"https://openalex.org/W7161059029","doi":"https://doi.org/10.48550/arxiv.2605.12139","title":"BoolXLLM: LLM-Assisted Explainability for Boolean Models","display_name":"BoolXLLM: LLM-Assisted Explainability for Boolean Models","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161059029","doi":"https://doi.org/10.48550/arxiv.2605.12139"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.12139","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12139","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.2605.12139","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136062506","display_name":"Du Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001309771","display_name":"Serdar Kad\u0131o\u011flu","orcid":"https://orcid.org/0000-0002-4672-6830"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kadioglu, Serdar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136070955","display_name":"Xin Eric Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xin","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9546999931335449,"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":0.9546999931335449,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.004999999888241291,"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/T10028","display_name":"Topic Modeling","score":0.003800000064074993,"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/interpretability","display_name":"Interpretability","score":0.870199978351593},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.47699999809265137},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4300000071525574},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.41290000081062317},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4065000116825104},{"id":"https://openalex.org/keywords/boolean-model","display_name":"Boolean model","score":0.3862999975681305},{"id":"https://openalex.org/keywords/boolean-data-type","display_name":"Boolean data type","score":0.36640000343322754}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.870199978351593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6606000065803528},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48080000281333923},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4375999867916107},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C67499762","wikidata":"https://www.wikidata.org/wiki/Q4943358","display_name":"Boolean model","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C7342684","wikidata":"https://www.wikidata.org/wiki/Q520777","display_name":"Boolean data type","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C158465420","wikidata":"https://www.wikidata.org/wiki/Q1979515","display_name":"Boolean expression","level":3,"score":0.3407999873161316},{"id":"https://openalex.org/C39685927","wikidata":"https://www.wikidata.org/wiki/Q173183","display_name":"Boolean algebra","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C68481662","wikidata":"https://www.wikidata.org/wiki/Q176197","display_name":"Standard Boolean model","level":5,"score":0.28600001335144043},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26919999718666077},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C187455244","wikidata":"https://www.wikidata.org/wiki/Q942353","display_name":"Boolean function","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.12139","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12139","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.2605.12139","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12139","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7723392248153687}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Interpretable":[0],"machine":[1],"learning":[2],"aims":[3],"to":[4,167],"provide":[5],"transparent":[6],"models":[7,194],"whose":[8],"decision-making":[9],"processes":[10],"can":[11],"be":[12],"readily":[13],"understood":[14],"by":[15],"humans.":[16],"Recent":[17],"advances":[18],"in":[19,43],"rule-based":[20,91],"approaches,":[21],"such":[22],"as":[23,66],"expressive":[24,89],"Boolean":[25,81,90,130],"formulas":[26],"(BoolXAI),":[27],"offer":[28],"faithful":[29,148],"and":[30,50,123,127,141,165],"compact":[31],"representations":[32],"of":[33,80,107,188],"model":[34],"behavior.":[35],"However,":[36],"for":[37,120,195],"non-technical":[38],"stakeholders,":[39],"main":[40],"challenges":[41],"remain":[42],"practice:":[44],"(i)":[45],"selecting":[46],"semantically":[47,116],"meaningful":[48,117],"features":[49],"(ii)":[51],"translating":[52],"formal":[53],"logical":[54],"rules":[55,131],"into":[56,76,134],"accessible":[57,166],"explanations.":[58],"In":[59],"this":[60],"work,":[61],"we":[62],"propose":[63,115],"BoolXLLM":[64],",":[65,87],"a":[67],"hybrid":[68],"framework":[69],"that":[70,160,173],"integrates":[71],"Large":[72],"Language":[73],"Models":[74],"(LLMs)":[75],"the":[77,105,186],"end-to-end":[78],"pipeline":[79],"rule":[82,125],"learning.":[83],"We":[84],"augment":[85],"BoolXAI":[86],"an":[88,156],"classifier,":[92],"with":[93,150,192],"LLMs":[94,103,114],"at":[95,138],"three":[96],"critical":[97],"stages:":[98],"(1)":[99],"feature":[100],"selection,":[101],"where":[102,113,129],"guide":[104],"identification":[106],"domain-relevant":[108],"variables;":[109],"(2)":[110],"threshold":[111],"recommendation,":[112],"discretization":[118],"strategies":[119],"numerical":[121],"features;":[122],"(3)":[124],"compression":[126],"interpretation,":[128],"are":[132],"translated":[133],"natural":[135],"language":[136],"explanations":[137,149],"both":[139,162],"global":[140],"local":[142],"levels.":[143],"This":[144,153],"integration":[145],"bridges":[146],"formal,":[147],"human-understandable":[151],"narratives.":[152],"allows":[154],"build":[155],"explainable":[157],"AI":[158],"system":[159],"is":[161],"theoretically":[163],"grounded":[164],"non-experts.":[168],"Early":[169],"empirical":[170],"results":[171],"demonstrate":[172],"LLM-assisted":[174],"pipelines":[175],"improve":[176],"interpretability":[177],"while":[178],"maintaining":[179],"competitive":[180],"predictive":[181],"performance.":[182],"Our":[183],"work":[184],"highlights":[185],"promise":[187],"combining":[189],"symbolic":[190],"reasoning":[191],"language-based":[193],"human-centered":[196],"explainability.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-14T00:00:00"}
