{"id":"https://openalex.org/W7134911388","doi":"https://doi.org/10.1109/icdmw69685.2025.00350","title":"GEM-Style Constraints for PEFT with Dual Gradient Projection in LoRA","display_name":"GEM-Style Constraints for PEFT with Dual Gradient Projection in LoRA","publication_year":2025,"publication_date":"2025-11-12","ids":{"openalex":"https://openalex.org/W7134911388","doi":"https://doi.org/10.1109/icdmw69685.2025.00350"},"language":null,"primary_location":{"id":"doi:10.1109/icdmw69685.2025.00350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw69685.2025.00350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining Workshops (ICDMW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128716079","display_name":"Brian Tekmen","orcid":null},"institutions":[{"id":"https://openalex.org/I169335092","display_name":"University of North Carolina at Greensboro","ror":"https://ror.org/04fnxsj42","country_code":"US","type":"education","lineage":["https://openalex.org/I169335092"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Brian Tekmen","raw_affiliation_strings":["University of North Carolina Greensboro,Department of Computer Science,Greensboro,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina Greensboro,Department of Computer Science,Greensboro,USA","institution_ids":["https://openalex.org/I169335092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128764280","display_name":"Jason Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Yin","raw_affiliation_strings":["North Carolina State University,Department of Computer Science,Raleigh,USA"],"affiliations":[{"raw_affiliation_string":"North Carolina State University,Department of Computer Science,Raleigh,USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128787859","display_name":"Qianqian Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I169335092","display_name":"University of North Carolina at Greensboro","ror":"https://ror.org/04fnxsj42","country_code":"US","type":"education","lineage":["https://openalex.org/I169335092"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qianqian Tong","raw_affiliation_strings":["University of North Carolina Greensboro,Department of Computer Science,Greensboro,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina Greensboro,Department of Computer Science,Greensboro,USA","institution_ids":["https://openalex.org/I169335092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5128716079"],"corresponding_institution_ids":["https://openalex.org/I169335092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75991112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2736","last_page":"2743"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.10920000076293945,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.10920000076293945,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10739","display_name":"Electromagnetic Scattering and Analysis","score":0.037700001150369644,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11216","display_name":"Radiation Detection and Scintillator Technologies","score":0.03579999879002571,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.48080000281333923},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.37049999833106995},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3481999933719635},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.3479999899864197},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.31139999628067017}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49559998512268066},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44519999623298645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41130000352859497},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3707999885082245},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3481999933719635},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3422999978065491},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdmw69685.2025.00350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw69685.2025.00350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Data Mining Workshops (ICDMW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4587021768093109,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1682403713","https://openalex.org/W2013439434","https://openalex.org/W2033511209","https://openalex.org/W2060277733","https://openalex.org/W2098132613","https://openalex.org/W2100556411","https://openalex.org/W2124541940","https://openalex.org/W2136885855","https://openalex.org/W2560647685","https://openalex.org/W2769646558","https://openalex.org/W2964189064","https://openalex.org/W2996514457","https://openalex.org/W3030364939","https://openalex.org/W3046814132","https://openalex.org/W4236362309","https://openalex.org/W4244393449","https://openalex.org/W4250589301","https://openalex.org/W4390660936","https://openalex.org/W4392173735","https://openalex.org/W4396875110"],"related_works":[],"abstract_inverted_index":{"Full":[0],"fine-tuning":[1],"of":[2],"LLMs":[3],"is":[4],"costly,":[5],"motivating":[6],"continual":[7],"learning":[8],"(CL)":[9],"with":[10,46,58],"parameter-efficient":[11],"adapters.":[12],"We":[13],"revisit":[14],"Gradient":[15],"Episodic":[16],"Memory":[17],"(GEM)":[18],"in":[19,40],"the":[20],"Low-Rank":[21],"Adapter":[22],"(LoRA)":[23],"subspace":[24],"and":[25,85,105],"introduce":[26],"I-GEM,":[27],"a":[28,53,122],"fixed-budget,":[29],"GPU-resident":[30],"dual":[31],"projected-gradient":[32],"approximation":[33],"to":[34,125],"GEM's":[35,77],"quadratic":[36],"projection.":[37],"Constraining":[38],"non-interference":[39],"adapter":[41],"parameters":[42],"preserves":[43],"GEM-like":[44],"behavior":[45],"orders-of-magnitude":[47],"lower":[48],"mean":[49],"projection":[50,96],"overhead.":[51],"On":[52],"3-task":[54],"AG":[55],"News":[56],"split":[57],"induced":[59],"domain":[60],"drift,":[61],"using":[62],"GPT-2":[63],"(<tex":[64,72],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[65,73,81,90,102,108],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\text{3":[66],"5":[67,68],"M}$</tex>)":[69],"+":[70],"LoRA":[71],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathrm{r}=\\mathrm{8}$</tex>),":[74],"I-GEM":[75],"matches":[76],"AvgAcc":[78],"(within":[79],"<tex":[80,89,101,107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\sim":[82,91,103,109],"0.04$</tex>":[83],"pts)":[84],"outperforms":[86],"A-GEM":[87],"by":[88,100],"1.4$</tex>":[92],"pts,":[93],"while":[94],"reducing":[95],"time":[97],"vs.":[98],"GEM":[99,119],"10^{3}$</tex>":[104],"remaining":[106],"10":[110],"\\times$</tex>":[111],"slower":[112],"than":[113],"A-GEM.":[114],"These":[115],"results":[116],"suggest":[117],"LoRA-space":[118],"constraints":[120],"are":[121],"practical":[123],"path":[124],"CL":[126],"at":[127],"LLM":[128],"scale.":[129]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2026-03-12T00:00:00"}