{"id":"https://openalex.org/W7129580547","doi":"https://doi.org/10.48550/arxiv.2602.14160","title":"Process-Supervised Multi-Agent Reinforcement Learning for Reliable Clinical Reasoning","display_name":"Process-Supervised Multi-Agent Reinforcement Learning for Reliable Clinical Reasoning","publication_year":2026,"publication_date":"2026-02-15","ids":{"openalex":"https://openalex.org/W7129580547","doi":"https://doi.org/10.48550/arxiv.2602.14160"},"language":"en","primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.14160","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126183790","display_name":"Chaeeun Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Chaeeun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126202180","display_name":"T. Michael Yates","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yates, T. Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126244516","display_name":"Pasquale Minervini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minervini, Pasquale","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126173418","display_name":"T. Ian Simpson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Simpson, T. Ian","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15729802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11642","display_name":"Genomics and Rare Diseases","score":0.2874999940395355,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11642","display_name":"Genomics and Rare Diseases","score":0.2874999940395355,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.17649999260902405,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.15189999341964722,"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/supervisor","display_name":"Supervisor","score":0.9032999873161316},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.6976000070571899},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6413999795913696},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6201000213623047},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6029000282287598},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.474700003862381},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.3808000087738037},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.328900009393692}],"concepts":[{"id":"https://openalex.org/C2779110517","wikidata":"https://www.wikidata.org/wiki/Q1240788","display_name":"Supervisor","level":2,"score":0.9032999873161316},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.6976000070571899},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6413999795913696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6402999758720398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6270999908447266},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6201000213623047},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6029000282287598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4844000041484833},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.474700003862381},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3808000087738037},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.328900009393692},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.3027999997138977},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2736999988555908},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2700999975204468},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2551000118255615}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.14160","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/2483b658-f4c7-4a09-b655-312b54239bcc","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/2483b658-f4c7-4a09-b655-312b54239bcc","pdf_url":null,"source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lee, C, Yates, T M, Minervini, P & Simpson, T I 2026 'Process-supervised multi-agent reinforcement learning for reliable clinical reasoning' pp. 1-26. https://doi.org/10.48550/arXiv.2602.14160","raw_type":"workingPaper"},{"id":"doi:10.48550/arxiv.2602.14160","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14160","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":"pmh:doi:10.48550/arxiv.2602.14160","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6618959307670593,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Clinical":[0],"decision-making":[1],"requires":[2],"nuanced":[3],"reasoning":[4,28,79],"over":[5],"heterogeneous":[6],"evidence":[7],"and":[8,84],"traceable":[9],"justifications.":[10],"While":[11],"recent":[12],"LLM":[13],"multi-agent":[14,91],"systems":[15],"(MAS)":[16],"show":[17],"promise,":[18],"they":[19],"largely":[20],"optimise":[21],"for":[22,68],"outcome":[23,114,137,145],"accuracy":[24,115,146],"while":[25,148],"overlooking":[26],"process-grounded":[27],"aligned":[29],"with":[30,71,101,105,118,134,140],"clinical":[31,82],"standards.":[32],"One":[33],"critical":[34],"real-world":[35],"case":[36],"of":[37],"this":[38,69],"is":[39,50,158],"gene-disease":[40],"validity":[41],"curation,":[42],"where":[43],"experts":[44],"must":[45],"determine":[46],"whether":[47],"a":[48,54,89,106,119],"gene":[49],"causally":[51],"implicated":[52],"in":[53,127],"disease":[55],"by":[56],"synthesising":[57],"diverse":[58],"biomedical":[59],"evidence.":[60],"We":[61],"introduce":[62],"an":[63],"agent-as-tool":[64],"reinforcement":[65],"learning":[66],"framework":[67],"task":[70],"two":[72],"objectives:":[73],"(i)":[74],"process-level":[75],"supervision":[76],"to":[77,123,153],"ensure":[78],"follows":[80],"valid":[81],"pathways,":[83],"(ii)":[85],"efficient":[86],"coordination":[87],"via":[88],"hierarchical":[90],"system.":[92],"Our":[93,156],"evaluation":[94],"on":[95],"the":[96],"ClinGen":[97],"dataset":[98],"shows":[99],"that":[100],"outcome-only":[102],"rewards,":[103,138],"MAS":[104,139],"GRPO-trained":[107,141],"Qwen3-4B":[108],"supervisor":[109,122,142],"agent":[110],"substantially":[111],"improves":[112],"final":[113],"from":[116],"0.195":[117],"base":[120],"model":[121],"0.732,":[124],"but":[125],"results":[126],"poor":[128],"process":[129,135,151],"alignment":[130],"(0.392":[131],"F1).":[132],"Conversely,":[133],"+":[136],"achieves":[143],"higher":[144],"(0.750)":[147],"significantly":[149],"improving":[150],"fidelity":[152],"0.520":[154],"F1.":[155],"code":[157],"available":[159],"at":[160],"https://github.com/chaeeunlee-io/GeneDiseaseCurationAgents.":[161]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-02-18T00:00:00"}