{"id":"https://openalex.org/W7160925795","doi":"https://doi.org/10.3390/info17050460","title":"Parameter-Efficient Fine-Tuning via General Linear Structural Regularization for High-Rank Adaptation","display_name":"Parameter-Efficient Fine-Tuning via General Linear Structural Regularization for High-Rank Adaptation","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160925795","doi":"https://doi.org/10.3390/info17050460"},"language":"en","primary_location":{"id":"doi:10.3390/info17050460","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17050460","pdf_url":"https://www.mdpi.com/2078-2489/17/5/460/pdf?version=1778314199","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/17/5/460/pdf?version=1778314199","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136000938","display_name":"Bo Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhao","raw_affiliation_strings":["School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028245257","display_name":"Weihua Ou","orcid":"https://orcid.org/0000-0001-5241-7703"},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihua Ou","raw_affiliation_strings":["School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550025, China","institution_ids":["https://openalex.org/I154893126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5028245257"],"corresponding_institution_ids":["https://openalex.org/I154893126"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55916626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"5","first_page":"460","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1370999962091446,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1370999962091446,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.09430000185966492,"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"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.08160000294446945,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/bottleneck","display_name":"Bottleneck","score":0.8300999999046326},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7351999878883362},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5425999760627747},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/information-bottleneck-method","display_name":"Information bottleneck method","score":0.4426000118255615},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.40630000829696655},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4007999897003174}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8300999999046326},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7351999878883362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5723999738693237},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.558899998664856},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.4426000118255615},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.40630000829696655},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4007999897003174},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C49766605","wikidata":"https://www.wikidata.org/wiki/Q207643","display_name":"Linear map","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C147060835","wikidata":"https://www.wikidata.org/wiki/Q1757151","display_name":"Krylov subspace","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35359999537467957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31610000133514404},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C6802819","wikidata":"https://www.wikidata.org/wiki/Q1072174","display_name":"Linear system","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2854999899864197}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info17050460","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17050460","pdf_url":"https://www.mdpi.com/2078-2489/17/5/460/pdf?version=1778314199","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:379954a0a8ed4f66b4d7ef6ab4a26bbb","is_oa":true,"landing_page_url":"https://doaj.org/article/379954a0a8ed4f66b4d7ef6ab4a26bbb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 17, Iss 5, p 460 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info17050460","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info17050460","pdf_url":"https://www.mdpi.com/2078-2489/17/5/460/pdf?version=1778314199","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3753124090","display_name":null,"funder_award_id":"QJJ[2024]009","funder_id":"https://openalex.org/F4320326674","funder_display_name":"Department of Education of Guizhou Province"},{"id":"https://openalex.org/G4300404550","display_name":null,"funder_award_id":"QJJ [2023] 011","funder_id":"https://openalex.org/F4320326674","funder_display_name":"Department of Education of Guizhou Province"},{"id":"https://openalex.org/G7784321418","display_name":null,"funder_award_id":"62262005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326674","display_name":"Department of Education of Guizhou Province","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160925795.pdf","grobid_xml":"https://content.openalex.org/works/W7160925795.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1546425147","https://openalex.org/W2889787757","https://openalex.org/W3034457116","https://openalex.org/W3174770825","https://openalex.org/W4205508242","https://openalex.org/W4205991051","https://openalex.org/W4389520299","https://openalex.org/W7133233472"],"related_works":[],"abstract_inverted_index":{"Parameter-efficient":[0],"fine-tuning":[1],"(PEFT)":[2],"enables":[3],"large":[4],"language":[5],"models":[6],"to":[7,9,71,102,178,185,193,198,204,215,226],"adapt":[8],"downstream":[10,155],"tasks":[11,156],"with":[12,171],"low":[13],"computational":[14],"cost.":[15],"As":[16],"a":[17,32,44,88,104],"representative":[18],"high-rank":[19],"PEFT":[20],"method,":[21],"MoRA":[22,95,164],"(High-Rank":[23],"Updating":[24],"for":[25],"Parameter-Efficient":[26],"Fine-Tuning)":[27],"improves":[28,115,174,189],"update":[29,77],"expressiveness":[30,120],"through":[31],"compression\u2013transformation\u2013decompression":[33],"reparameterization":[34],"mechanism.":[35],"However,":[36],"its":[37],"bottleneck":[38,62,96],"subspace":[39,67,97,119],"is":[40],"still":[41],"modeled":[42],"using":[43],"freely":[45],"learned":[46],"linear":[47,91],"transformation.":[48],"In":[49,109],"addition,":[50],"grouped":[51],"compression":[52],"may":[53,65],"project":[54],"information":[55],"from":[56,176,183,191,196,202,213,223],"different":[57],"original":[58],"directions":[59],"into":[60,93],"shared":[61],"coordinates.":[63],"This":[64],"reduce":[66],"separability":[68],"and":[69,98,118,142,157,180,200],"lead":[70],"inefficient":[72],"utilization":[73],"of":[74],"the":[75,94,112,150,166,207],"effective":[76],"space.":[78],"To":[79],"address":[80],"this":[81,110],"limitation,":[82],"we":[83],"propose":[84],"GL-log-MoRA,":[85],"which":[86],"introduces":[87],"learnable":[89],"general":[90],"transformation":[92],"applies":[99],"log-determinant":[100],"regularization":[101],"encourage":[103],"more":[105],"balanced":[106],"spectral":[107],"structure.":[108],"way,":[111],"proposed":[113],"method":[114],"directional":[116],"coordination":[117],"without":[121],"imposing":[122],"hard":[123],"structural":[124],"constraints":[125],"or":[126],"causing":[127],"noticeable":[128],"memory":[129,219],"overhead.":[130],"We":[131],"evaluate":[132],"GL-log-MoRA":[133,148,173],"on":[134,153],"five":[135],"benchmarks:":[136],"LogiQA,":[137],"Financial":[138,181],"PhraseBank,":[139],"GSM8K,":[140],"FinQA,":[141],"HotpotQA.":[143],"The":[144],"results":[145],"show":[146],"that":[147],"achieves":[149],"best":[151],"performance":[152],"these":[154],"yields":[158],"small":[159],"but":[160],"consistent":[161],"improvements":[162],"over":[163],"under":[165],"same":[167],"parameter":[168],"budget.":[169],"Compared":[170],"MoRA,":[172],"LogiQA":[175],"42.50%":[177],"45.45%":[179],"PhraseBank":[182],"81.60%":[184],"83.02%.":[186],"It":[187],"also":[188],"GSM8K":[190],"63.1%":[192],"64.6%,":[194],"FinQA":[195],"10.02%":[197],"10.23%,":[199],"HotpotQA":[201],"70.6%":[203],"70.8%.":[205],"Meanwhile,":[206],"average":[208],"empirical":[209],"effective-rank":[210],"indicator":[211],"increases":[212],"1.05":[214],"2.80.":[216],"Peak":[217],"GPU":[218],"changes":[220],"only":[221],"slightly,":[222],"18.21":[224],"GB":[225],"18.28":[227],"GB.":[228]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-05-13T00:00:00"}