{"id":"https://openalex.org/W7160826997","doi":"https://doi.org/10.48550/arxiv.2605.07111","title":"Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation","display_name":"Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160826997","doi":"https://doi.org/10.48550/arxiv.2605.07111"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07111","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07111","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.2605.07111","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029366297","display_name":"Haozhan Tang","orcid":"https://orcid.org/0000-0001-6719-846X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Haozhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135906262","display_name":"Xiuqi Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Xiuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135907325","display_name":"Xinyin Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinyin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135832638","display_name":"Boxun Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Boxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135888449","display_name":"Virginia Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, Virginia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068640850","display_name":"Kevin Kuo","orcid":"https://orcid.org/0000-0001-7803-7901"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuo, Kevin","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":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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.544700026512146,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.544700026512146,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.11779999732971191,"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/T10028","display_name":"Topic Modeling","score":0.09179999679327011,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.6776999831199646},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5623999834060669},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.45730000734329224},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.4410000145435333},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.42489999532699585},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.38260000944137573},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3822000026702881}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8651000261306763},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.6776999831199646},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5623999834060669},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.4410000145435333},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3822000026702881},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3815000057220459},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3644999861717224},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3483000099658966},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2694000005722046},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.26930001378059387},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.26170000433921814},{"id":"https://openalex.org/C2779664074","wikidata":"https://www.wikidata.org/wiki/Q3518405","display_name":"Terminal (telecommunication)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C164155591","wikidata":"https://www.wikidata.org/wiki/Q2067766","display_name":"Satisfiability modulo theories","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07111","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07111","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.2605.07111","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07111","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":[{"display_name":"Quality Education","score":0.5021046996116638,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"literature":[1],"on":[2,78,171,197,201],"fine-tuning":[3],"Large":[4],"Language":[5],"Models":[6],"highlights":[7],"a":[8,40,91,99,155],"fundamental":[9],"debate.":[10],"While":[11],"Full":[12,96],"Fine-Tuning":[13],"(FFT)":[14],"provides":[15],"the":[16,119,177],"representational":[17],"plasticity":[18],"required":[19],"for":[20],"high-entropy":[21],"knowledge":[22],"injection,":[23],"Low-Rank":[24],"Adaptation":[25],"(LoRA)":[26],"can":[27],"match":[28],"or":[29,172],"surpass":[30],"FFT":[31,115,180],"performance":[32],"because":[33],"many":[34],"tasks":[35,54],"only":[36,151],"require":[37],"updates":[38,113,153],"in":[39],"low-rank":[41],"space":[42],"and":[43,58,61,67,73,95,116,150,181,199,203],"benefit":[44],"from":[45],"LoRA's":[46],"additional":[47],"regularization.":[48],"Through":[49],"empirical":[50],"evaluation":[51],"across":[52,183],"diverse":[53],"(SQL,":[55],"Medical":[56],"QA,":[57],"Counterfactual":[59],"Knowledge)":[60],"varying":[62,162],"language":[63],"models":[64],"(Gemma-3-1B,":[65],"Qwen2.5-1.5B,":[66],"Qwen2.5-3B),":[68],"we":[69,89,142],"verify":[70],"both":[71,107,131],"trends":[72],"demonstrate":[74],"that":[75,102,124,167],"relying":[76],"solely":[77],"either":[79,169],"static":[80],"architecture":[81],"is":[82,207],"structurally":[83],"limited.":[84],"To":[85],"address":[86],"this":[87],"challenge,":[88],"propose":[90],"Mixture":[92],"of":[93,157,160,176,179],"LoRA":[94,117,158,182,191],"(MoLF)":[97],"Fine-Tuning,":[98],"unified":[100],"framework":[101],"enables":[103],"continuous":[104],"navigation":[105],"between":[106,114],"training":[108,137],"regimes.":[109],"MoLF":[110,168],"dynamically":[111],"routes":[112,152],"at":[118,209],"optimizer":[120],"level":[121],"to":[122,130,195],"ensure":[123],"exact":[125],"gradient":[126],"signals":[127],"are":[128],"available":[129],"experts":[132,159],"throughout":[133],"training,":[134],"yielding":[135],"stable":[136],"dynamics.":[138],"For":[139],"memory-constrained":[140],"environments,":[141],"also":[143],"introduce":[144],"MoLF-Efficient,":[145],"which":[146],"freezes":[147],"base":[148],"weights":[149],"among":[154],"pair":[156],"potentially":[161],"rank.":[163],"Our":[164,205],"evaluations":[165],"show":[166],"improves":[170],"stays":[173],"within":[174],"$1.5\\%$":[175],"better":[178],"all":[184],"settings,":[185],"while":[186],"MoLF-Efficient":[187],"outperforms":[188],"prior":[189],"adaptive":[190],"approaches":[192],"by":[193],"up":[194],"$20\\%$":[196],"Fact":[198],"$9\\%$":[200],"Med":[202],"SQL.":[204],"code":[206],"open-sourced":[208],"https://github.com/11785T23/molf.git.":[210]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-12T00:00:00"}
