{"id":"https://openalex.org/W7124999214","doi":"https://doi.org/10.1109/bsn66969.2025.11337685","title":"SenseCF: LLM-Prompted Counterfactuals for Intervention and Sensor Data Augmentation","display_name":"SenseCF: LLM-Prompted Counterfactuals for Intervention and Sensor Data Augmentation","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W7124999214","doi":"https://doi.org/10.1109/bsn66969.2025.11337685"},"language":null,"primary_location":{"id":"doi:10.1109/bsn66969.2025.11337685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn66969.2025.11337685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Body Sensor Networks (BSN)","raw_type":"proceedings-article"},"type":"article","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/A5029066170","display_name":"Shovito Barua Soumma","orcid":"https://orcid.org/0009-0007-1949-9795"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shovito Barua Soumma","raw_affiliation_strings":["College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004"],"affiliations":[{"raw_affiliation_string":"College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039978080","display_name":"Asiful Arefeen","orcid":"https://orcid.org/0000-0002-7876-3206"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Asiful Arefeen","raw_affiliation_strings":["College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004"],"affiliations":[{"raw_affiliation_string":"College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031734253","display_name":"Stephanie M. Carpenter","orcid":"https://orcid.org/0000-0003-4523-7565"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephanie M. Carpenter","raw_affiliation_strings":["College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004"],"affiliations":[{"raw_affiliation_string":"College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123378297","display_name":"Melanie Hingle","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Melanie Hingle","raw_affiliation_strings":["School of Nutritional Sciences and Wellness, University of Arizona,Tucson,AZ,USA"],"affiliations":[{"raw_affiliation_string":"School of Nutritional Sciences and Wellness, University of Arizona,Tucson,AZ,USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007139473","display_name":"Hassan Ghasemzadeh","orcid":"https://orcid.org/0000-0002-1844-1416"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassan Ghasemzadeh","raw_affiliation_strings":["College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004"],"affiliations":[{"raw_affiliation_string":"College of Health Solutions, Arizona State University,Phoenix,AZ,USA,85004","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029066170"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":2.3568,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9335709,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.5232999920845032,"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":0.5232999920845032,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.2542000114917755,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.09969999641180038,"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/robustness","display_name":"Robustness (evolution)","score":0.6344000101089478},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.6025999784469604},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.5059000253677368},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.47350001335144043},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46970000863075256},{"id":"https://openalex.org/keywords/psychological-intervention","display_name":"Psychological intervention","score":0.4180999994277954},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.34279999136924744},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.33959999680519104}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6344000101089478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6205000281333923},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.6025999784469604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5910000205039978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5708000063896179},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.5059000253677368},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46970000863075256},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3776000142097473},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3513999879360199},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C79897977","wikidata":"https://www.wikidata.org/wiki/Q5054568","display_name":"Causal chain","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2994107952","wikidata":"https://www.wikidata.org/wiki/Q1814351","display_name":"Public health interventions","level":3,"score":0.2596000134944916},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bsn66969.2025.11337685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn66969.2025.11337685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Body Sensor Networks (BSN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4021420184","display_name":null,"funder_award_id":"IIS-2402650","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4640661259","display_name":null,"funder_award_id":"T32DK137525","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2945295328","https://openalex.org/W3155445702","https://openalex.org/W4386122647","https://openalex.org/W4406457873"],"related_works":[],"abstract_inverted_index":{"Counterfactual":[0],"explanations":[1],"(CFs)":[2],"offer":[3],"human-centric":[4],"insights":[5],"into":[6],"machine":[7],"learning":[8],"predictions":[9],"by":[10],"highlighting":[11],"minimal":[12],"changes":[13],"required":[14],"to":[15,81,98,103,137],"alter":[16],"an":[17],"outcome.":[18],"Therefore,":[19],"CFs":[20,51,111],"can":[21],"be":[22],"used":[23],"as":[24,85,112],"(i)":[25],"interventions":[26],"for":[27,34,49,69,76],"abnormality":[28],"prevention":[29],"and":[30,55,72,88,105,140,144],"(ii)":[31],"augmented":[32,113],"data":[33],"training":[35],"robust":[36],"models.":[37],"In":[38],"this":[39],"work,":[40],"we":[41],"explore":[42],"large":[43],"language":[44],"models":[45],"(LLMs),":[46],"specifically":[47],"GPT-4o-mini,":[48],"generating":[50],"in":[52,126,142],"a":[53,73],"zero-shot":[54],"three-shot":[56],"setting.":[57],"We":[58],"evaluate":[59],"our":[60,90],"approach":[61,93],"on":[62],"two":[63],"datasets:":[64],"the":[65,131],"AI-Readi":[66],"flagship":[67],"dataset":[68,75],"stress":[70],"prediction":[71,146],"public":[74],"heart":[77],"disease":[78],"detection.":[79],"Compared":[80],"traditional":[82],"methods":[83],"such":[84],"DiCE,":[86],"CFNOW,":[87],"NICE,":[89],"few-shot":[91],"LLM-based":[92],"achieves":[94],"high":[95],"plausibility":[96],"(up":[97,102],"99%),":[99],"strong":[100],"validity":[101],"0.99),":[104],"competitive":[106],"sparsity.":[107],"Moreover,":[108],"using":[109],"LLM-generated":[110],"samples":[114],"improves":[115],"downstream":[116],"classifier":[117],"performance":[118],"(an":[119],"average":[120],"accuracy":[121],"gain":[122],"of":[123,133],"5%),":[124],"especially":[125],"low-data":[127],"regimes.":[128],"This":[129],"demonstrates":[130],"potential":[132],"prompt-based":[134],"generative":[135],"techniques":[136],"enhance":[138],"explainability":[139],"robustness":[141],"clinical":[143],"physiological":[145],"tasks.":[147],"Code":[148],"base:":[149],"github.com/shovito66/SenseCF.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-21T00:00:00"}