{"id":"https://openalex.org/W4415428631","doi":"https://doi.org/10.3233/faia250973","title":"Prediction Is Not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings","display_name":"Prediction Is Not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428631","doi":"https://doi.org/10.3233/faia250973"},"language":null,"primary_location":{"id":"doi:10.3233/faia250973","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250973","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia250973","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119739171","display_name":"Hanna Herasimchyk","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hanna Herasimchyk","raw_affiliation_strings":["Universit\u00e4t Hamburg, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Hamburg, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095900417","display_name":"Alhassan Abdelhalim","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alhassan Abdelhalim","raw_affiliation_strings":["Universit\u00e4t Hamburg, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Hamburg, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095900418","display_name":"S\u00f6ren Laue","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"S\u00f6ren Laue","raw_affiliation_strings":["Universit\u00e4t Hamburg, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Hamburg, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5095900416","display_name":"Michaela Regneri","orcid":null},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michaela Regneri","raw_affiliation_strings":["Universit\u00e4t Hamburg, Hamburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e4t Hamburg, Hamburg, Germany","institution_ids":["https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I159176309"],"apc_list":null,"apc_paid":null,"fwci":30.8873,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.99133212,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.51419997215271,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.51419997215271,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/interpretability","display_name":"Interpretability","score":0.866599977016449},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6545000076293945},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5467000007629395},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.483599990606308},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4650000035762787},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.45170000195503235},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.42750000953674316},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.39739999175071716}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.866599977016449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689300000667572},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6545000076293945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6503000259399414},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6190000176429749},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5467000007629395},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.483599990606308},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4650000035762787},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.45170000195503235},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.42750000953674316},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26159998774528503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia250973","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250973","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia250973","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia250973","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"what":[1],"knowledge":[2,27],"is":[3,10,142],"implicitly":[4],"encoded":[5,28],"in":[6,29,123],"deep":[7],"learning":[8],"models":[9,39],"essential":[11],"for":[12],"improving":[13],"the":[14,26,67,72,75,108,124,146,165],"interpretability":[15],"of":[16,36,49,168],"AI":[17],"systems.":[18],"This":[19],"paper":[20],"examines":[21],"common":[22],"methods":[23,42,99],"to":[24],"explain":[25],"word":[30,68,125,147],"embeddings,":[31],"which":[32,140],"are":[33,110],"core":[34],"elements":[35],"large":[37],"language":[38],"(LLMs).":[40],"These":[41],"typically":[43],"involve":[44],"mapping":[45],"embeddings":[46,69,73],"onto":[47],"collections":[48],"human-interpretable":[50],"semantic":[51,64,121,169],"features,":[52],"known":[53],"as":[54],"feature":[55],"norms.":[56],"Prior":[57],"work":[58],"assumes":[59],"that":[60,71,84,97,107,152],"accurately":[61],"predicting":[62],"these":[63,98],"features":[65],"from":[66],"implies":[70],"contain":[74],"corresponding":[76],"knowledge.":[77],"We":[78,95],"challenge":[79],"this":[80],"assumption":[81],"by":[82,113,145],"demonstrating":[83],"prediction":[85,134],"accuracy":[86],"alone":[87],"does":[88],"not":[89,137],"reliably":[90,138],"indicate":[91,139],"genuine":[92,166],"feature-based":[93],"interpretability.":[94],"show":[96],"can":[100],"successfully":[101],"predict":[102],"even":[103],"random":[104],"information,":[105],"concluding":[106],"results":[109],"predominantly":[111],"determined":[112],"an":[114],"algorithmic":[115],"upper":[116],"bound":[117],"rather":[118,162],"than":[119,163],"meaningful":[120],"representation":[122],"embeddings.":[126,148],"Consequently,":[127],"comparisons":[128],"between":[129],"datasets":[130],"based":[131],"solely":[132],"on":[133],"performance":[135],"do":[136],"dataset":[141],"better":[143],"captured":[144],"Our":[149],"analysis":[150],"illustrates":[151],"such":[153],"mappings":[154],"primarily":[155],"reflect":[156],"geometric":[157],"similarity":[158],"within":[159],"vector":[160],"spaces":[161],"indicating":[164],"emergence":[167],"properties.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-24T00:00:00"}