{"id":"https://openalex.org/W7125489509","doi":"https://doi.org/10.48550/arxiv.2601.15745","title":"Hallucination Mitigating for Medical Report Generation","display_name":"Hallucination Mitigating for Medical Report Generation","publication_year":2026,"publication_date":"2026-01-22","ids":{"openalex":"https://openalex.org/W7125489509","doi":"https://doi.org/10.48550/arxiv.2601.15745"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.15745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15745","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","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.2601.15745","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101319161","display_name":"Ruoqing Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Ruoqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123694467","display_name":"Runze Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Runze","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123716690","display_name":"Piji Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Piji","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3463999927043915,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.3463999927043915,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10028","display_name":"Topic Modeling","score":0.20180000364780426,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.05590000003576279,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/natural-language-generation","display_name":"Natural language generation","score":0.6740999817848206},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5648999810218811},{"id":"https://openalex.org/keywords/realm","display_name":"Realm","score":0.47369998693466187},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.4674000144004822},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.44760000705718994},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3799000084400177}],"concepts":[{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.6740999817848206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6442999839782715},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5648999810218811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4885999858379364},{"id":"https://openalex.org/C2778757428","wikidata":"https://www.wikidata.org/wiki/Q1250464","display_name":"Realm","level":2,"score":0.47369998693466187},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.44760000705718994},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40860000252723694},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.3723999857902527},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3504999876022339},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.34880000352859497},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3077999949455261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3027999997138977},{"id":"https://openalex.org/C2985722590","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medical knowledge","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27000001072883606},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.262800008058548},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.2547999918460846},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.15745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15745","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.15745","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15745","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7884476184844971,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,62],"the":[1,8,22,27,55,80,85,88,116,123,145,161],"realm":[2],"of":[3,10,24,60,147,163],"medical":[4],"report":[5,171],"generation":[6],"(MRG),":[7],"integration":[9],"natural":[11,39],"language":[12,34],"processing":[13],"has":[14],"emerged":[15],"as":[16,50],"a":[17,67,103,110],"vital":[18],"tool":[19],"to":[20,43,78,87,114,122,132],"alleviate":[21],"workload":[23],"radiologists.":[25],"Despite":[26],"impressive":[28],"capabilities":[29],"demonstrated":[30],"by":[31,90],"large":[32],"vision":[33],"models":[35,135],"(LVLMs)":[36],"in":[37,54,136,166],"understanding":[38],"language,":[40],"their":[41],"susceptibility":[42],"generating":[44,137],"plausible":[45],"yet":[46],"inaccurate":[47],"claims,":[48],"known":[49],"``hallucinations'',":[51],"raises":[52],"concerns-especially":[53],"nuanced":[56],"and":[57,140,157,169],"critical":[58],"field":[59],"medical.":[61],"this":[63],"work,":[64],"we":[65,128],"introduce":[66,109],"framework,":[68],"\\textbf{K}nowledge-\\textbf{E}nhanced":[69],"with":[70,150],"Fine-Grained":[71],"\\textbf{R}einforced":[72],"Rewards":[73],"\\textbf{M}edical":[74],"Report":[75],"Generation":[76],"(KERM),":[77],"tackle":[79],"issue.":[81],"Our":[82],"approach":[83,165],"refines":[84],"input":[86],"LVLM":[89],"first":[91],"utilizing":[92],"MedCLIP":[93],"for":[94],"knowledge":[95,105,118],"retrieval,":[96],"incorporating":[97],"relevant":[98,121,142],"lesion":[99],"fact":[100],"sentences":[101],"from":[102],"curated":[104],"corpus.":[106],"We":[107],"then":[108],"novel":[111],"purification":[112],"module":[113],"ensure":[115],"retrieved":[117],"is":[119],"contextually":[120],"patient's":[124],"clinical":[125],"context.":[126],"Subsequently,":[127],"employ":[129],"fine-grained":[130],"rewards":[131],"guide":[133],"these":[134],"highly":[138],"supportive":[139],"clinically":[141],"descriptions,":[143],"ensuring":[144],"alignment":[146],"model's":[148],"outputs":[149],"desired":[151],"behaviors.":[152],"Experimental":[153],"results":[154],"on":[155],"IU-Xray":[156],"MIMIC-CXR":[158],"datasets":[159],"validate":[160],"effectiveness":[162],"our":[164],"mitigating":[167],"hallucinations":[168],"enhancing":[170],"quality.":[172]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-01-24T00:00:00"}