{"id":"https://openalex.org/W7155544179","doi":"https://doi.org/10.1109/icsc67292.2026.00018","title":"Faithful or Plausible? A Counterfactual Analysis of LLM-Generated Explanations for Machine Learning Models","display_name":"Faithful or Plausible? A Counterfactual Analysis of LLM-Generated Explanations for Machine Learning Models","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7155544179","doi":"https://doi.org/10.1109/icsc67292.2026.00018"},"language":null,"primary_location":{"id":"doi:10.1109/icsc67292.2026.00018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc67292.2026.00018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Semantic Computing (ICSC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134471741","display_name":"Shaun Colegado","orcid":null},"institutions":[{"id":"https://openalex.org/I43369023","display_name":"California State University, San Bernardino","ror":"https://ror.org/02n651896","country_code":"US","type":"education","lineage":["https://openalex.org/I43369023"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaun Colegado","raw_affiliation_strings":["California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States","institution_ids":["https://openalex.org/I43369023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134472751","display_name":"Jennifer Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I43369023","display_name":"California State University, San Bernardino","ror":"https://ror.org/02n651896","country_code":"US","type":"education","lineage":["https://openalex.org/I43369023"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Jin","raw_affiliation_strings":["California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States","institution_ids":["https://openalex.org/I43369023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121069748","display_name":"Yunfei Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I43369023","display_name":"California State University, San Bernardino","ror":"https://ror.org/02n651896","country_code":"US","type":"education","lineage":["https://openalex.org/I43369023"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunfei Hou","raw_affiliation_strings":["California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"California State University, San Bernardino,School of Computer Science and Engineering,San Bernardino,United States","institution_ids":["https://openalex.org/I43369023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I43369023"],"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":"83","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.8335000276565552,"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":0.8335000276565552,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.05429999902844429,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.04100000113248825,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7322999835014343},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.30480000376701355},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.25780001282691956},{"id":"https://openalex.org/keywords/computational-learning-theory","display_name":"Computational learning theory","score":0.257099986076355}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7322999835014343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6208000183105469},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5347999930381775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5020999908447266},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23489999771118164},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2296999990940094},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2281000018119812}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsc67292.2026.00018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc67292.2026.00018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Semantic Computing (ICSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2954503794","https://openalex.org/W3034917890","https://openalex.org/W3035628711","https://openalex.org/W3212748247","https://openalex.org/W4376643691","https://openalex.org/W4385571986","https://openalex.org/W4388640086","https://openalex.org/W4391428762","https://openalex.org/W4400123667","https://openalex.org/W4400461591","https://openalex.org/W4404782636","https://openalex.org/W7116962968","https://openalex.org/W7120088840"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,10],"models":[2,48,151],"(LLMs)":[3],"are":[4,86],"increasingly":[5],"used":[6],"to":[7,25,35],"generate":[8],"natural":[9],"explanations":[11,41,92,111],"of":[12,39,145,149],"predictive":[13,66,150],"machine":[14],"learning":[15],"models,":[16],"yet":[17],"their":[18],"outputs":[19],"often":[20,109],"emphasize":[21],"plausibility":[22],"over":[23],"faithfulness":[24,100,163],"the":[26,37,113,140,143],"underlying":[27],"model":[28,84,96,123],"logic.":[29],"This":[30],"study":[31],"applies":[32],"counterfactual":[33,72,154],"testing":[34,155],"evaluate":[36],"fidelity":[38],"LLM":[40],"in":[42,65,80,164],"a":[43,57,157],"structured":[44],"setting:":[45],"decision":[46,116],"tree":[47],"predicting":[49],"customer":[50],"churn":[51],"(i.e.,":[52],"when":[53,120],"customers":[54],"stop":[55],"using":[56],"company\u2019s":[58],"product":[59],"or":[60],"service-a":[61],"classic":[62],"benchmark":[63],"problem":[64],"modeling":[67],"research).":[68],"We":[69],"design":[70],"two":[71],"tests":[73],"across":[74],"four":[75],"prompting":[76],"strategies":[77],"that":[78,94],"vary":[79],"whether":[81],"dataset":[82,102],"and/or":[83],"information":[85],"provided.":[87],"Results":[88],"from":[89],"1,200":[90],"generated":[91],"show":[93],"supplying":[95],"context":[97,103],"substantially":[98],"improves":[99],"whereas":[101],"provides":[104],"little":[105],"benefit,":[106],"and":[107,142,152],"LLMs":[108,125,146],"broaden":[110],"beyond":[112],"model\u2019s":[114],"true":[115],"path.":[117],"Notably,":[118],"even":[119],"given":[121],"full":[122],"logic,":[124],"remain":[126],"predisposed":[127],"toward":[128],"generating":[129],"plausible":[130],"rather":[131],"than":[132],"strictly":[133],"faithful":[134],"explanations.":[135],"These":[136],"findings":[137],"highlight":[138],"both":[139],"promise":[141],"limits":[144],"as":[147,156],"interpreters":[148],"introduce":[153],"potential":[158],"framework":[159],"for":[160],"evaluating":[161],"explanation":[162],"data-heavy":[165],"contexts.":[166]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-25T00:00:00"}