{"id":"https://openalex.org/W7133333692","doi":"https://doi.org/10.48550/arxiv.2603.01625","title":"Measuring What VLMs Don't Say: Validation Metrics Hide Clinical Terminology Erasure in Radiology Report Generation","display_name":"Measuring What VLMs Don't Say: Validation Metrics Hide Clinical Terminology Erasure in Radiology Report Generation","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133333692","doi":"https://doi.org/10.48550/arxiv.2603.01625"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01625","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.01625","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127877021","display_name":"Aditya Parikh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Parikh, Aditya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Feragen, Aasa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feragen, Aasa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035293526","display_name":"Sneha Das","orcid":"https://orcid.org/0000-0002-4017-1280"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Sneha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058891617","display_name":"Stella Frank","orcid":"https://orcid.org/0009-0004-7443-3156"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frank, Stella","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/T11894","display_name":"Radiology practices and education","score":0.4982999861240387,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11894","display_name":"Radiology practices and education","score":0.4982999861240387,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.2644999921321869,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.03310000151395798,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/terminology","display_name":"Terminology","score":0.5936999917030334},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.569599986076355},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5493999719619751},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5263000130653381},{"id":"https://openalex.org/keywords/erasure","display_name":"Erasure","score":0.4205999970436096},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.3968999981880188},{"id":"https://openalex.org/keywords/standardization","display_name":"Standardization","score":0.3935999870300293},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.37950000166893005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6840999722480774},{"id":"https://openalex.org/C547195049","wikidata":"https://www.wikidata.org/wiki/Q1725664","display_name":"Terminology","level":2,"score":0.5936999917030334},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.569599986076355},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5493999719619751},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45649999380111694},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4237000048160553},{"id":"https://openalex.org/C2778790127","wikidata":"https://www.wikidata.org/wiki/Q484885","display_name":"Erasure","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C188087704","wikidata":"https://www.wikidata.org/wiki/Q369577","display_name":"Standardization","level":2,"score":0.3935999870300293},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.37950000166893005},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37380000948905945},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.36970001459121704},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3549000024795532},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3093999922275543},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2946999967098236},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2648000121116638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01625","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.01625","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01625","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"deployment":[1],"of":[2,37,141,159],"Vision-Language":[3],"Models":[4],"(VLMs)":[5],"in":[6,31,52,110,114],"radiology":[7],"requires":[8],"validation":[9],"metrics":[10],"that":[11,40,76,107,135],"go":[12],"beyond":[13],"surface-level":[14],"text":[15,60],"similarity":[16],"to":[17,42,49,71,91,124],"ensure":[18],"clinical":[19,63,96,127],"fidelity":[20],"and":[21,61],"demographic":[22,131],"fairness.":[23],"This":[24],"paper":[25],"investigates":[26],"a":[27,104,156],"critical":[28],"blind":[29,67],"spot":[30,68],"current":[32],"model":[33,93],"evaluation:":[34],"the":[35,126],"use":[36],"decoding":[38,137],"strategies":[39],"lead":[41,70],"high":[43,139],"aggregate":[44],"token-overlap":[45],"scores":[46],"despite":[47],"succumbing":[48],"template":[50],"collapse,":[51],"which":[53],"models":[54,75],"generate":[55],"only":[56],"repetitive,":[57],"safe":[58],"generic":[59],"omit":[62],"terminology.":[64],"Unaddressed,":[65],"this":[66],"can":[69],"metric":[72],"gaming,":[73],"where":[74],"perform":[77],"well":[78],"on":[79],"benchmarks":[80],"prove":[81],"clinically":[82],"uninformative.":[83],"Instead,":[84],"we":[85],"advocate":[86],"for":[87,95],"lexical":[88],"diversity":[89],"measures":[90],"check":[92],"generations":[94],"specificity.":[97],"We":[98,133],"introduce":[99],"Clinical":[100],"Association":[101,118],"Displacement":[102],"(CAD),":[103],"vocabulary-level":[105],"framework":[106],"quantifies":[108],"shifts":[109,123],"demographic-based":[111],"word":[112],"associations":[113],"generated":[115],"reports.":[116],"Weighted":[117],"Erasure":[119],"(WAE)":[120],"aggregates":[121],"these":[122],"measure":[125],"signal":[128],"loss":[129],"across":[130],"groups.":[132],"show":[134],"deterministic":[136],"produces":[138],"levels":[140],"semantic":[142],"erasure,":[143],"while":[144],"stochastic":[145],"sampling":[146],"generates":[147],"diverse":[148],"outputs":[149],"but":[150],"risks":[151],"introducing":[152],"new":[153],"bias,":[154],"motivating":[155],"fundamental":[157],"rethink":[158],"how":[160],"\"optimal\"":[161],"reporting":[162],"is":[163],"defined.":[164]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-04T00:00:00"}