{"id":"https://openalex.org/W7161748745","doi":"https://doi.org/10.48550/arxiv.2605.17101","title":"SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning","display_name":"SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning","publication_year":2026,"publication_date":"2026-05-16","ids":{"openalex":"https://openalex.org/W7161748745","doi":"https://doi.org/10.48550/arxiv.2605.17101"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17101","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":"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.2605.17101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136482270","display_name":"Yongfeng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yongfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136458435","display_name":"Ruiying Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Ruiying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136475201","display_name":"James Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, James","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/T10028","display_name":"Topic Modeling","score":0.8844000101089478,"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/T10028","display_name":"Topic Modeling","score":0.8844000101089478,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.029500000178813934,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.014999999664723873,"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/workflow","display_name":"Workflow","score":0.7131999731063843},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5658000111579895},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.4652999937534332},{"id":"https://openalex.org/keywords/obsolescence","display_name":"Obsolescence","score":0.4278999865055084},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.41600000858306885},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.37540000677108765},{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.36800000071525574},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.36320000886917114}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7609999775886536},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7131999731063843},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48980000615119934},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C30795975","wikidata":"https://www.wikidata.org/wiki/Q282744","display_name":"Obsolescence","level":2,"score":0.4278999865055084},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38109999895095825},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.37540000677108765},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C122783720","wikidata":"https://www.wikidata.org/wiki/Q183065","display_name":"Interpreter","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C204434341","wikidata":"https://www.wikidata.org/wiki/Q357789","display_name":"Adjudication","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32420000433921814},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3197999894618988},{"id":"https://openalex.org/C130191384","wikidata":"https://www.wikidata.org/wiki/Q2996887","display_name":"Copycat","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C3019659195","wikidata":"https://www.wikidata.org/wiki/Q5690566","display_name":"Meaningful use","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C111640148","wikidata":"https://www.wikidata.org/wiki/Q847349","display_name":"Rubric","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17101","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":"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.2605.17101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17101","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":"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"is":[3,88],"widely":[4],"employed":[5],"to":[6,58,89,119],"mitigate":[7],"risks":[8],"such":[9],"as":[10],"hallucinations":[11],"and":[12,49,84,96,137,144,150],"knowledge":[13],"obsolescence":[14],"in":[15],"medical":[16,112],"question":[17,113],"answering,":[18,114],"yet":[19],"its":[20],"predominantly":[21],"single-round,":[22],"static":[23],"retrieval":[24,50],"paradigm":[25],"misaligns":[26],"with":[27,78],"the":[28,91,123,130,138,156],"multi-stage":[29],"process":[30],"of":[31,81],"clinical":[32,127],"reasoning.":[33],"This":[34],"compressed":[35],"workflow":[36,92],"induces":[37],"two":[38],"structural":[39],"deficiencies:":[40],"question-to-query":[41],"translation":[42],"often":[43],"lacks":[44,51],"clinically":[45],"grounded":[46],"semantic":[47],"interpretation,":[48,82,129],"iterative":[52],"sufficiency":[53],"feedback,":[54],"making":[55],"it":[56],"difficult":[57],"form":[59],"reliable":[60],"evidence":[61,142],"chains.":[62],"We":[63],"argue":[64],"that":[65],"both":[66],"issues":[67],"stem":[68],"from":[69],"a":[70,74,106],"deeper":[71],"cause:":[72],"overloading":[73],"single":[75],"reasoning":[76],"chain":[77],"heterogeneous":[79],"tasks":[80],"exploration,":[83],"adjudication.":[85],"The":[86],"remedy":[87],"reconstruct":[90],"via":[93],"task":[94],"decoupling":[95],"dynamic":[97],"multi-round":[98],"exploration.":[99],"To":[100],"this":[101],"end,":[102],"we":[103],"propose":[104],"SEMA-RAG,":[105],"Self-Evolving":[107],"Multi-Agent":[108],"RAG":[109],"framework":[110],"for":[111,126,133,141],"which":[115],"assigns":[116],"these":[117],"roles":[118],"three":[120],"specialist":[121],"agents:":[122],"Interpreter":[124],"Agent":[125,132,140],"schema":[128],"Explorer":[131],"sufficiency-driven":[134],"self-evolving":[135],"retrieval,":[136],"Arbiter":[139],"adjudication":[143],"answer":[145],"selection.":[146],"Across":[147],"five":[148,151],"benchmarks":[149],"LLM":[152],"backbones,":[153],"SEMA-RAG":[154],"improves":[155],"strongest":[157],"baseline":[158],"by":[159],"+6.46":[160],"accuracy":[161],"points":[162],"on":[163],"average,":[164],"measured":[165],"per":[166],"backbone.":[167]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}
