{"id":"https://openalex.org/W4412888439","doi":"https://doi.org/10.18653/v1/2025.findings-acl.549","title":"Towards Conditioning Clinical Text Generation for User Control","display_name":"Towards Conditioning Clinical Text Generation for User Control","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888439","doi":"https://doi.org/10.18653/v1/2025.findings-acl.549"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.549","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.549","pdf_url":"https://aclanthology.org/2025.findings-acl.549.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.549.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093129962","display_name":"Osman Alperen Kora\u015f","orcid":"https://orcid.org/0009-0006-6490-3139"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Osman Alperen Kora\u015f","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119181423","display_name":"Rabi Bahnan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rabi Bahnan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017161970","display_name":"Jens Kleesiek","orcid":"https://orcid.org/0000-0001-8686-0682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jens Kleesiek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007940140","display_name":"Amin Dada","orcid":"https://orcid.org/0000-0003-4016-7799"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amin Dada","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":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10549","last_page":"10569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9233999848365784,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9233999848365784,"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/computer-science","display_name":"Computer science","score":0.6135348081588745},{"id":"https://openalex.org/keywords/conditioning","display_name":"Conditioning","score":0.587067186832428},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5780044198036194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.264426052570343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10488659143447876},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08556896448135376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6135348081588745},{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.587067186832428},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5780044198036194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.264426052570343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10488659143447876},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08556896448135376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.549","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.549","pdf_url":"https://aclanthology.org/2025.findings-acl.549.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.549","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.549","pdf_url":"https://aclanthology.org/2025.findings-acl.549.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888439.pdf","grobid_xml":"https://content.openalex.org/works/W4412888439.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2344176346","https://openalex.org/W2052307325","https://openalex.org/W1489675464","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345"],"abstract_inverted_index":{"Deploying":[0],"natural":[1],"language":[2],"generation":[3,101],"systems":[4],"in":[5,12],"clinical":[6,99],"settings":[7],"remains":[8],"challenging":[9],"despite":[10],"advances":[11],"Large":[13],"Language":[14],"Models":[15],"(LLMs),":[16],"which":[17],"continue":[18],"to":[19,38,80,104],"exhibit":[20],"hallucinations":[21],"and":[22,78,108],"factual":[23,109],"inconsistencies,":[24],"necessitating":[25],"human":[26,36,85],"oversight.This":[27],"paper":[28],"explores":[29],"automated":[30],"dataset":[31,83],"augmentation":[32],"using":[33],"LLMs":[34,40],"as":[35],"proxies":[37],"condition":[39],"for":[41,102],"clinician":[42],"control":[43,103],"without":[44,75],"increasing":[45],"cognitive":[46],"workload.On":[47],"the":[48,89,95],"BioNLP":[49],"ACL'24":[50],"Discharge":[51],"Me!":[52],"Shared":[53],"Task,":[54],"we":[55],"achieve":[56],"new":[57],"state-of-the-art":[58],"results":[59],"with":[60,82],"simpler":[61],"methods":[62],"than":[63],"prior":[64],"submissions":[65],"through":[66],"more":[67],"efficient":[68],"training,":[69],"yielding":[70],"a":[71],"9%":[72],"relative":[73],"improvement":[74],"augmented":[76],"training":[77],"up":[79],"34%":[81],"augmentation.Preliminary":[84],"evaluation":[86],"further":[87],"supports":[88],"effectiveness":[90],"of":[91,97],"our":[92],"approach,":[93],"highlighting":[94],"potential":[96],"augmenting":[98],"text":[100],"enhance":[105],"relevance,":[106],"accuracy,":[107],"consistency.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}