{"id":"https://openalex.org/W7163685697","doi":"https://doi.org/10.48550/arxiv.2606.05693","title":"MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry","display_name":"MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry","publication_year":2026,"publication_date":"2026-06-04","ids":{"openalex":"https://openalex.org/W7163685697","doi":"https://doi.org/10.48550/arxiv.2606.05693"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05693","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":null,"license_id":null,"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.2606.05693","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137996847","display_name":"Joey Chan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chan, Joey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052506681","display_name":"Wonbin Kweon","orcid":"https://orcid.org/0000-0002-8813-3179"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kweon, Wonbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111126308","display_name":"Ashley Shin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shin, Ashley","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042355857","display_name":"Niharika Bhattacharjee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhattacharjee, Niharika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137936875","display_name":"Pengcheng Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Pengcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137980243","display_name":"Yue Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137918179","display_name":"Jiawei Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jiawei","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":0.5450999736785889,"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":0.5450999736785889,"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":0.38940000534057617,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.01549999974668026,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.7371000051498413},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6180999875068665},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5570999979972839},{"id":"https://openalex.org/keywords/chemical-space","display_name":"Chemical space","score":0.4339999854564667},{"id":"https://openalex.org/keywords/molecular-descriptor","display_name":"Molecular descriptor","score":0.3968000113964081},{"id":"https://openalex.org/keywords/molecular-model","display_name":"Molecular model","score":0.39149999618530273},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.325300008058548}],"concepts":[{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.7371000051498413},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6180999875068665},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5570999979972839},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5231000185012817},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.4440999925136566},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.4339999854564667},{"id":"https://openalex.org/C164923092","wikidata":"https://www.wikidata.org/wiki/Q3705921","display_name":"Molecular descriptor","level":3,"score":0.3968000113964081},{"id":"https://openalex.org/C178910836","wikidata":"https://www.wikidata.org/wiki/Q2196961","display_name":"Molecular model","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38359999656677246},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C32909587","wikidata":"https://www.wikidata.org/wiki/Q11369","display_name":"Molecule","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3043999969959259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27160000801086426},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.2596000134944916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05693","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.05693","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05693","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6809200048446655,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1,32],"models":[2,151,156],"(LLMs)":[3],"have":[4],"shown":[5],"promise":[6],"for":[7,56,187],"molecular":[8,22,58,101,162,176],"property":[9,59,102,177],"prediction,":[10],"but":[11],"their":[12],"ability":[13],"to":[14,119,132,135],"reason":[15],"over":[16],"chemical":[17,44,190],"structures":[18],"remains":[19],"limited,":[20],"as":[21,25],"representations":[23],"such":[24],"SMILES":[26],"differ":[27],"substantially":[28],"from":[29,92,159],"the":[30,93,143],"natural":[31],"on":[33,123],"which":[34],"LLMs":[35],"are":[36],"primarily":[37],"trained.":[38],"To":[39],"bridge":[40],"this":[41],"semantic":[42],"and":[43,84,87,108,126,152],"knowledge":[45,191],"gap,":[46],"we":[47],"propose":[48],"MolE-RAG,":[49],"a":[50,136,184],"training-free,":[51],"molecule-centric":[52,171],"retrieval-augmented":[53],"generation":[54],"framework":[55,186],"LLM-based":[57,175],"prediction.":[60],"MolE-RAG":[61,98,114],"augments":[62],"each":[63,146],"prediction":[64,103,178],"with":[65,154],"three":[66],"complementary":[67],"sources":[68],"of":[69,145],"inference-time":[70],"context:":[71],"retrieved":[72,91],"chemistry":[73],"literature,":[74],"molecule-specific":[75],"information":[76],"including":[77],"compound":[78],"synonyms,":[79],"identifiers,":[80],"functional":[81],"group":[82],"annotations,":[83],"physicochemical":[85],"descriptors,":[86],"structurally":[88],"similar":[89],"molecules":[90],"training":[94],"set.":[95],"We":[96,139],"evaluate":[97],"across":[99,150],"nine":[100],"tasks":[104,125],"using":[105],"proprietary,":[106],"chemistry-specialized,":[107],"open-source":[109],"LLMs.":[110],"Across":[111],"general-purpose":[112],"LLMs,":[113],"improves":[115],"ROC-AUC":[116],"by":[117,130],"up":[118,131],"28":[120],"percentage":[121],"points":[122],"classification":[124],"reduces":[127],"regression":[128],"RMSE":[129],"67%":[133],"relative":[134],"SMILES-only":[137],"baseline.":[138],"further":[140],"find":[141],"that":[142,170],"utility":[144],"context":[147],"source":[148],"varies":[149],"tasks,":[153],"different":[155],"benefiting":[157],"most":[158],"textual":[160],"retrieval,":[161],"context,":[163],"or":[164],"structural":[165],"retrieval.":[166],"These":[167],"results":[168],"suggest":[169],"retrieval":[172],"can":[173],"improve":[174],"without":[179],"model":[180],"fine-tuning":[181],"while":[182],"providing":[183],"flexible":[185],"integrating":[188],"heterogeneous":[189],"at":[192],"inference":[193],"time.":[194]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-06T00:00:00"}
