{"id":"https://openalex.org/W7131386163","doi":"https://doi.org/10.48550/arxiv.2602.20449","title":"Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference","display_name":"Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference","publication_year":2026,"publication_date":"2026-02-24","ids":{"openalex":"https://openalex.org/W7131386163","doi":"https://doi.org/10.48550/arxiv.2602.20449"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.20449","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","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/A5125483411","display_name":"Anna Hart","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hart, Anna","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084181962","display_name":"Chi Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Chi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126779581","display_name":"Jeonghwan Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jeonghwan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126798856","display_name":"Huimin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Huimin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126840416","display_name":"Heng Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Heng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5125483411"],"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.6593000292778015,"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"}},"topics":[{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.6593000292778015,"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"}},{"id":"https://openalex.org/T11642","display_name":"Genomics and Rare Diseases","score":0.05829999968409538,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.05429999902844429,"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/inference","display_name":"Inference","score":0.6541000008583069},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5622000098228455},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5584999918937683},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5285999774932861},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4729999899864197},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44020000100135803},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.3912000060081482},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.3400000035762787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239999771118164},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6541000008583069},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5622000098228455},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5285999774932861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5218999981880188},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4729999899864197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46380001306533813},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.3912000060081482},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.33550000190734863},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C39608478","wikidata":"https://www.wikidata.org/wiki/Q5015979","display_name":"Cache language model","level":5,"score":0.26330000162124634}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.20449","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.20449","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.20449","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.20449","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.776718258857727,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"Protein":[1],"Language":[2],"Models":[3],"(PLMs)":[4],"apply":[5],"transformer-based":[6,53],"model":[7,136],"architectures":[8,54],"from":[9,30,142,162],"natural":[10,31,96,109],"language":[11,26,97,110,193,205],"processing":[12],"to":[13,68,112,137,164],"biological":[14,208],"sequences,":[15],"predicting":[16],"a":[17,35,40,102],"variety":[18],"of":[19,42,83,88,118,146,188],"protein":[20,25,59,94,129,140,154,201],"functions":[21],"and":[22,61,95,124,153,178,203],"properties.":[23],"However,":[24],"has":[27],"key":[28],"differences":[29,48],"language,":[32],"such":[33],"as":[34],"rich":[36],"functional":[37],"space":[38],"despite":[39],"vocabulary":[41],"only":[43],"20":[44],"amino":[45],"acids.":[46],"These":[47],"motivate":[49],"research":[50,189],"into":[51,199],"how":[52,62,80,192],"operate":[55],"differently":[56],"in":[57,107,128,207],"the":[58,81,93,108,116,135,143,147,150,200],"domain":[60,111,202],"we":[63,75,100],"can":[64],"better":[65],"leverage":[66],"PLMs":[67,148],"solve":[69],"protein-related":[70],"tasks.":[71,181],"In":[72],"this":[73],"work,":[74],"begin":[76],"by":[77,133,172],"directly":[78,190],"comparing":[79,191],"distribution":[82],"information":[84],"stored":[85],"across":[86,176],"layers":[87,145],"attention":[89],"heads":[90],"differs":[91],"between":[92],"domain.":[98],"Furthermore,":[99],"adapt":[101],"simple":[103],"early-exit":[104],"technique-originally":[105],"used":[106],"improve":[113],"efficiency":[114,126,171],"at":[115,155],"cost":[117],"performance-to":[119],"achieve":[120,158],"both":[121],"increased":[122],"accuracy":[123],"substantial":[125],"gains":[127,160],"non-structural":[130,179],"property":[131],"prediction":[132,180],"allowing":[134],"automatically":[138],"select":[139],"representations":[141],"intermediate":[144],"for":[149],"specific":[151],"task":[152],"hand.":[156],"We":[157],"performance":[159],"ranging":[161],"0.4":[163],"7.01":[165],"percentage":[166],"points":[167],"while":[168],"simultaneously":[169],"improving":[170],"over":[173],"10":[174],"percent":[175],"models":[177,194],"Our":[182],"work":[183],"opens":[184],"up":[185],"an":[186],"area":[187],"change":[195],"behavior":[196],"when":[197],"moved":[198],"advances":[204],"modeling":[206],"domains.":[209]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-26T00:00:00"}