{"id":"https://openalex.org/W7161153088","doi":"https://doi.org/10.48550/arxiv.2605.12736","title":"ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis","display_name":"ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161153088","doi":"https://doi.org/10.48550/arxiv.2605.12736"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.12736","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12736","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.2605.12736","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113076190","display_name":"Mohammad Jahid Ibna Basher","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Basher, Mohammad Jahid Ibna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093219806","display_name":"Ali Khodabandeh Yalabadi","orcid":"https://orcid.org/0009-0009-4310-0259"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yalabadi, Ali Khodabandeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135338317","display_name":"Ivan Garibay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garibay, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062903281","display_name":"\u00d6zlem \u00d6zmen Garibay","orcid":"https://orcid.org/0000-0001-9215-694X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garibay, Ozlem Ozmen","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/T11948","display_name":"Machine Learning in Materials Science","score":0.8787999749183655,"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":0.8787999749183655,"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":0.03689999878406525,"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":0.0071000000461936,"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/template","display_name":"Template","score":0.6784999966621399},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6252999901771545},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6144999861717224},{"id":"https://openalex.org/keywords/retrosynthetic-analysis","display_name":"Retrosynthetic analysis","score":0.5995000004768372},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.492900013923645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4519999921321869},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.6784999966621399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.628600001335144},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6252999901771545},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6144999861717224},{"id":"https://openalex.org/C42437451","wikidata":"https://www.wikidata.org/wiki/Q902227","display_name":"Retrosynthetic analysis","level":3,"score":0.5995000004768372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573199987411499},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.492900013923645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4519999921321869},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3853999972343445},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3741999864578247},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3610999882221222},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.12736","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12736","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.2605.12736","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12736","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":{"Template":[0],"based":[1,32,84,211],"single":[2],"step":[3],"retrosynthesis":[4,85],"predicts":[5],"reactants":[6],"by":[7,92],"selecting":[8],"and":[9,110,223,242],"applying":[10],"an":[11],"explicit":[12,232],"reaction":[13,111,176],"template,":[14],"making":[15],"each":[16],"prediction":[17,46,213],"traceable":[18],"to":[19,67,70,102,180,190],"a":[20,54,77,104,125,142,195],"chemical":[21],"transformation":[22],"rule.":[23],"This":[24],"is":[25,47,64,214],"useful":[26],"for":[27,150],"synthesis":[28],"planning,":[29],"but":[30,69],"template":[31,41,45,83,89,116,132,148,158,185,212],"methods":[33],"are":[34,244],"often":[35],"viewed":[36],"as":[37,50,86],"less":[38],"competitive":[39],"than":[40,235],"free":[42],"models":[43],"because":[44],"commonly":[48],"formulated":[49],"global":[51],"classification":[52],"over":[53,118],"long":[55,218],"tailed":[56],"rule":[57],"library.":[58],"We":[59,74,206],"argue":[60],"that":[61,81,209,224],"this":[62],"weakness":[63],"not":[65],"inherent":[66],"templates,":[68,222],"the":[71,156,161,165,217,237],"learning":[72],"formulation.":[73],"present":[75],"ConRetroBert,":[76],"dual":[78],"encoder":[79,149,159],"framework":[80],"reframes":[82],"dense":[87],"product":[88],"retrieval":[90,151,210],"followed":[91],"candidate":[93,122,171],"set":[94,172],"listwise":[95,128],"ranking.":[96],"Stage":[97,113,169],"1":[98],"uses":[99,141],"contrastive":[100],"pretraining":[101],"learn":[103],"shared":[105],"embedding":[106],"space":[107],"between":[108],"products":[109],"templates.":[112],"2":[114,170],"refines":[115],"ranking":[117,162,173],"mined":[119],"hard":[120,137],"negative":[121,138],"sets":[123],"with":[124],"multi":[126],"positive":[127,239],"objective.":[129],"To":[130],"enable":[131],"side":[133],"adaptation":[134,186],"without":[135],"destabilizing":[136],"mining,":[139],"ConRetroBert":[140],"slow":[143],"moving":[144,146],"exponential":[145],"average":[147],"bank":[152],"construction":[153],"while":[154,182],"updating":[155],"live":[157],"through":[160],"loss.":[163],"On":[164],"local":[166],"USPTO-50k":[167],"benchmark,":[168],"improves":[174,188],"top-1":[175,202],"accuracy":[177,203],"from":[178,194,230],"50.5%":[179],"61.3%,":[181],"EMA":[183],"stabilized":[184],"further":[187],"it":[189],"62.4%.":[191],"Fine":[192],"tuning":[193],"leakage":[196],"controlled":[197],"USPTO-Full":[198],"checkpoint":[199],"reaches":[200],"75.4%":[201],"on":[204],"USPTO-50k.":[205],"also":[207],"show":[208],"strong":[215],"in":[216],"tail":[219],"of":[220],"rare":[221],"many":[225],"correct":[226],"reactant":[227],"predictions":[228],"arise":[229],"alternative":[231],"templates":[233],"rather":[234],"only":[236],"recorded":[238],"label.":[240],"Code":[241],"data":[243],"available":[245],"at":[246],"https://github.com/JahidBasher/ConRetroBert.":[247]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-15T00:00:00"}