{"id":"https://openalex.org/W7128785562","doi":"https://doi.org/10.48550/arxiv.2602.12162","title":"Amortized Molecular Optimization via Group Relative Policy Optimization","display_name":"Amortized Molecular Optimization via Group Relative Policy Optimization","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128785562","doi":"https://doi.org/10.48550/arxiv.2602.12162"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.12162","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":"preprint","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/A5125956530","display_name":"Muhammad bin Javaid","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Javaid, Muhammad bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125953034","display_name":"Hasham Hussain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hussain, Hasham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125929806","display_name":"Ashima Khanna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khanna, Ashima","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074303246","display_name":"Berke Kisin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kisin, Berke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125933874","display_name":"Jonathan Pirnay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pirnay, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125916651","display_name":"Alexander Mitsos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mitsos, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125971864","display_name":"Dominik G. Grimm","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Grimm, Dominik G.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125914386","display_name":"Martin Grohe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Grohe, Martin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5125956530"],"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/T11948","display_name":"Machine Learning in Materials Science","score":0.7778000235557556,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.7778000235557556,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.07069999724626541,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.042500000447034836,"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/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.5939000248908997},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5372999906539917},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.454800009727478},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.43709999322891235},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.39419999718666077}],"concepts":[{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.5939000248908997},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5372999906539917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4767000079154968},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4731999933719635},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.454800009727478},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3779999911785126},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32850000262260437},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26969999074935913},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.12162","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":"doi:10.48550/arxiv.2602.12162","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.12162","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.12162","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"structurally":[1,132],"constrained":[2,133],"molecular":[3,70],"optimization,":[4],"state-of-the-art":[5],"methods":[6,45,109,163],"restart":[7],"an":[8,59],"expensive":[9,28],"oracle-driven":[10],"search":[11],"from":[12],"scratch":[13],"for":[14,85],"every":[15],"new":[16],"input":[17],"structure,":[18],"scaling":[19],"poorly":[20],"to":[21,47,49,111,180],"settings":[22],"with":[23,77],"many":[24],"starting":[25,98,127],"structures":[26,71],"or":[27],"oracles.":[29],"While":[30],"amortized":[31,60,86,150,162],"approaches":[32],"that":[33,64,92],"learn":[34],"a":[35,73,142,176],"transferable":[36],"policy":[37],"could":[38],"in":[39,72,88],"principle":[40],"remove":[41],"this":[42,89,104,116],"bottleneck,":[43],"existing":[44],"struggle":[46],"generalize":[48],"diverse":[50],"structural":[51],"constraints":[52],"at":[53,187],"inference":[54],"time.":[55],"We":[56,100,129],"present":[57],"AMORTIX,":[58],"Graph":[61],"Transformer":[62],"model":[63],"natively":[65],"supports":[66],"such":[67],"constraints,":[68],"optimizing":[69],"single":[74],"forward":[75],"pass":[76],"zero":[78],"inference-time":[79],"oracle":[80],"calls.":[81],"A":[82],"central":[83],"challenge":[84],"training":[87],"domain":[90],"is":[91,185],"optimization":[93],"difficulty":[94],"varies":[95],"drastically":[96],"across":[97],"structures.":[99,183],"show":[101],"that,":[102],"under":[103],"heterogeneity,":[105],"standard":[106],"reinforcement":[107],"learning":[108],"fail":[110],"stabilize":[112],"training,":[113],"and":[114,135,140,151,158],"address":[115],"by":[117],"normalizing":[118],"rewards":[119],"within":[120],"groups":[121],"of":[122,175],"completions":[123],"sharing":[124],"the":[125,165,168],"same":[126],"structure.":[128],"evaluate":[130],"on":[131,141,154,164],"single-":[134],"multi-target":[136],"kinase":[137],"inhibitor":[138],"design,":[139],"few-shot":[143],"prodrug":[144,169],"case":[145,170],"study.":[146],"AMORTIX":[147],"outperforms":[148],"both":[149],"instance-optimization":[152],"baselines":[153],"goal-directed":[155],"scaffold":[156],"decoration":[157],"ranks":[159],"first":[160],"among":[161],"PMO":[166],"benchmark;":[167],"study":[171],"further":[172],"demonstrates":[173],"transfer":[174],"learned":[177],"modification":[178],"rule":[179],"unseen":[181],"drug":[182],"Code":[184],"available":[186],"https://github.com/Hash-hh/AMORTIX/.":[188]},"counts_by_year":[],"updated_date":"2026-05-12T06:07:45.972803","created_date":"2026-02-14T00:00:00"}