{"id":"https://openalex.org/W7106140387","doi":"https://doi.org/10.48550/arxiv.2511.14365","title":"The Tokenization Bottleneck: How Vocabulary Extension Improves Chemistry Representation Learning in Pretrained Language Models","display_name":"The Tokenization Bottleneck: How Vocabulary Extension Improves Chemistry Representation Learning in Pretrained Language Models","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7106140387","doi":"https://doi.org/10.48550/arxiv.2511.14365"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.14365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.14365","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.14365","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kalamkar, Prathamesh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalamkar, Prathamesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Letcher, Ned","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Letcher, Ned","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Chami, Meissane","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chami, Meissane","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lad, Sahger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lad, Sahger","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Mohanty, Shayan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohanty, Shayan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Pendse, Prasanna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pendse, Prasanna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"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":0.9308000206947327,"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":0.9308000206947327,"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":0.023399999365210533,"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/T10028","display_name":"Topic Modeling","score":0.010499999858438969,"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/vocabulary","display_name":"Vocabulary","score":0.7265999913215637},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5315999984741211},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.49950000643730164},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4970000088214874},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.43560001254081726},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.39169999957084656},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.38019999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758899986743927},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.7265999913215637},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7250999808311462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6628999710083008},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5485000014305115},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5315999984741211},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4970000088214874},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.38019999861717224},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.35359999537467957},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.3206000030040741},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2776235265","wikidata":"https://www.wikidata.org/wiki/Q18392052","display_name":"Fragment (logic)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C126706616","wikidata":"https://www.wikidata.org/wiki/Q2944660","display_name":"Lexical item","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.27410000562667847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.14365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.14365","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":"doi:10.48550/arxiv.2511.14365","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.14365","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7935354709625244,"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":{"The":[0],"application":[1],"of":[2,48,89,92,106],"large":[3],"language":[4,50],"models":[5],"(LLMs)":[6],"to":[7,23,40,79,100],"chemistry":[8],"is":[9],"frequently":[10],"hampered":[11],"by":[12,44,73],"a":[13,37,55,64,104],"\"tokenization":[14],"bottleneck\",":[15],"where":[16],"tokenizers":[17],"tuned":[18],"on":[19,76,103],"general-domain":[20],"text":[21,78],"tend":[22],"fragment":[24],"chemical":[25,108],"representations":[26],"such":[27],"as":[28],"SMILES":[29],"into":[30],"semantically":[31],"uninformative":[32],"sub-tokens.":[33],"This":[34],"paper":[35],"introduces":[36],"principled":[38],"methodology":[39,98],"resolve":[41],"this":[42,81,93],"bottleneck":[43],"unifying":[45],"the":[46,90],"representation":[47],"natural":[49],"and":[51],"molecular":[52],"structures":[53],"within":[54],"single":[56],"model.":[57],"Our":[58],"approach":[59],"involves":[60],"targeted":[61],"vocabulary":[62,67],"extension-augmenting":[63],"pretrained":[65],"LLM's":[66],"with":[68],"chemically":[69],"salient":[70],"tokens,":[71],"followed":[72],"continued":[74],"pretraining":[75],"chemistry-domain":[77],"integrate":[80],"new":[82],"knowledge.":[83],"We":[84],"provide":[85],"an":[86],"empirical":[87],"demonstration":[88],"effectiveness":[91],"strategy,":[94],"showing":[95],"that":[96],"our":[97],"leads":[99],"superior":[101],"performance":[102],"range":[105],"downstream":[107],"tasks.":[109]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-20T00:00:00"}