{"id":"https://openalex.org/W4391128935","doi":"https://doi.org/10.1109/ictc58733.2023.10391861","title":"Enhancing Fine-Tuning in Low Data Regime by Increasing Representation Entropy During Pre-Training Phase","display_name":"Enhancing Fine-Tuning in Low Data Regime by Increasing Representation Entropy During Pre-Training Phase","publication_year":2023,"publication_date":"2023-10-11","ids":{"openalex":"https://openalex.org/W4391128935","doi":"https://doi.org/10.1109/ictc58733.2023.10391861"},"language":"en","primary_location":{"id":"doi:10.1109/ictc58733.2023.10391861","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ictc58733.2023.10391861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5008654322","display_name":"Jaeill Kim","orcid":"https://orcid.org/0000-0002-1088-2882"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeill Kim","raw_affiliation_strings":["Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068183035","display_name":"Jungwook Shin","orcid":"https://orcid.org/0000-0001-9529-1442"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jungwook Shin","raw_affiliation_strings":["Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056032525","display_name":"Wonjong Rhee","orcid":"https://orcid.org/0000-0002-2590-8774"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wonjong Rhee","raw_affiliation_strings":["Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","Interdisciplinary Program in Artificial Intelligence (IPAI), Seoul National University, Seoul, Republic of Korea","Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Intelligence and Information,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Interdisciplinary Program in Artificial Intelligence (IPAI), Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Intelligence and Information, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139264467"],"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":"1319","last_page":"1321"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973999857902527,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9966999888420105,"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/computer-science","display_name":"Computer science","score":0.6569482684135437},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6475109457969666},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.49338141083717346},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4268963932991028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41942477226257324},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"Fine-tuning","score":0.41767966747283936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38133925199508667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6569482684135437},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6475109457969666},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.49338141083717346},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4268963932991028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41942477226257324},{"id":"https://openalex.org/C157524613","wikidata":"https://www.wikidata.org/wiki/Q2828883","display_name":"Fine-tuning","level":2,"score":0.41767966747283936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38133925199508667},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc58733.2023.10391861","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ictc58733.2023.10391861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 14th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1631356911","https://openalex.org/W2092939357","https://openalex.org/W2099111195","https://openalex.org/W3065974826","https://openalex.org/W4297808394","https://openalex.org/W4322718191","https://openalex.org/W4386113238"],"related_works":["https://openalex.org/W4390306690","https://openalex.org/W1969209172","https://openalex.org/W2062195135","https://openalex.org/W4385572141","https://openalex.org/W2795079307","https://openalex.org/W4380558612","https://openalex.org/W4387829178","https://openalex.org/W4226410230","https://openalex.org/W3163689946","https://openalex.org/W3007909076"],"abstract_inverted_index":{"The":[0],"strategy":[1],"of":[2,10,31,78,100,116,124],"training":[3,23],"a":[4,36,79],"new":[5],"model":[6,12],"through":[7],"the":[8,41,55,76,98,101,114,117,122],"fine-tuning":[9,92],"pre-trained":[11,80],"has":[13],"gained":[14],"considerable":[15],"prominence":[16],"due":[17],"to":[18,21,70],"its":[19],"potential":[20],"reduce":[22],"costs":[24],"or":[25],"enhance":[26],"performance.":[27],"However,":[28],"accomplishing":[29],"both":[30],"these":[32],"objectives":[33],"concurrently":[34],"presents":[35],"noteworthy":[37],"challenge.":[38],"To":[39],"address":[40],"challenge,":[42],"this":[43],"study":[44],"adopts":[45],"two":[46,102,118],"entropy":[47,57,65,104],"metrics,":[48],"which":[49],"can":[50,85],"be":[51,87],"seamlessly":[52],"integrated":[53],"into":[54],"cross":[56],"loss.":[58],"Our":[59],"approach":[60],"aims":[61],"at":[62],"increasing":[63],"representation":[64,77,109],"during":[66,90],"pre-training":[67],"phase,":[68],"leading":[69],"an":[71],"increased":[72,83],"information":[73,84],"encoded":[74],"in":[75,106,120,127],"model.":[81],"This":[82],"then":[86],"effectively":[88],"harnessed":[89],"subsequent":[91],"phase.":[93],"In":[94],"experiments,":[95],"we":[96,112],"substantiate":[97],"reliability":[99],"adopted":[103],"metrics":[105,119],"accurately":[107],"quantifying":[108],"entropy.":[110],"Moreover,":[111],"demonstrate":[113],"effectiveness":[115],"enhancing":[121],"performance":[123],"fine-tuning,":[125],"particularly":[126],"low":[128],"data":[129],"regime.":[130]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}