{"id":"https://openalex.org/W4416251912","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229108","title":"Distill the Best, Ignore the Rest: A Study in Latent Dataset Distillation on Core-Sets","display_name":"Distill the Best, Ignore the Rest: A Study in Latent Dataset Distillation on Core-Sets","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251912","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229108"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5069729032","display_name":"Brian B. Moser","orcid":"https://orcid.org/0000-0002-0290-7904"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Brian B. Moser","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI),Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029509133","display_name":"Federico Raue","orcid":"https://orcid.org/0000-0002-8604-6207"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Federico Raue","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI),Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013376237","display_name":"Tobias Christian Nauen","orcid":null},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias C. Nauen","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI),Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053202923","display_name":"Stanislav Frolov","orcid":"https://orcid.org/0000-0003-2700-5031"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stanislav Frolov","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI),Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073903451","display_name":"Andreas Dengel","orcid":"https://orcid.org/0000-0001-9532-286X"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Dengel","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI),Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33256026"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6330000162124634,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6330000162124634,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.09960000216960907,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.07020000368356705,"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/distillation","display_name":"Distillation","score":0.7314000129699707},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7111999988555908},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5860999822616577},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5285999774932861},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4323999881744385},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.33980000019073486}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7314000129699707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.711899995803833},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7111999988555908},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6840999722480774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6169000267982483},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5285999774932861},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4323999881744385},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.33980000019073486},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.32089999318122864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30640000104904175},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26980000734329224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2798836702","https://openalex.org/W2962770929","https://openalex.org/W3094502228","https://openalex.org/W3095809828","https://openalex.org/W4224952733","https://openalex.org/W4285981784","https://openalex.org/W4292787070","https://openalex.org/W4312412605","https://openalex.org/W4312933868","https://openalex.org/W4319300193","https://openalex.org/W4386075990","https://openalex.org/W4388240452","https://openalex.org/W4402727287","https://openalex.org/W4402794458","https://openalex.org/W4404725766"],"related_works":[],"abstract_inverted_index":{"Latent":[0],"dataset":[1,124,132,158],"distillation,":[2],"which":[3],"exploits":[4],"pre-trained":[5],"generative":[6,80],"priors,":[7,81],"has":[8],"gained":[9],"significant":[10,28,97],"interest":[11],"in":[12],"recent":[13],"years":[14],"because":[15],"it":[16],"can":[17],"be":[18],"applied":[19],"agnostic":[20],"to":[21,69,89,114,134],"any":[22],"distillation":[23,32,77,101],"algorithm":[24],"and":[25,36,79,147,156],"addresses":[26],"two":[27],"limitations":[29],"of":[30,99,129,143],"classical":[31,76],"algorithms:":[33],"cross-architecture":[34,148],"generalization":[35,91],"high-resolution":[37],"synthesis.":[38],"However,":[39],"existing":[40],"approaches":[41],"typically":[42],"distill":[43],"from":[44],"the":[45,130,141,151],"entire":[46],"dataset,":[47],"potentially":[48],"including":[49],"non-beneficial":[50],"samples.":[51],"We":[52],"introduce":[53],"a":[54,84,96,115],"novel":[55],"\"Prune":[56],"First,":[57],"Distill":[58],"After\"":[59],"framework":[60,107],"that":[61,87],"systematically":[62],"prunes":[63],"datasets":[64],"via":[65],"loss-based":[66],"sampling":[67],"prior":[68,133],"latent":[70],"distillation.":[71,135,159],"By":[72],"leveraging":[73],"pruning":[74],"before":[75],"techniques":[78],"we":[82],"create":[83],"representative":[85],"coreset":[86],"leads":[88],"enhanced":[90],"for":[92,153],"unseen":[93],"architectures":[94],"-":[95],"challenge":[98],"current":[100],"methods.":[102],"More":[103],"specifically,":[104],"our":[105,137,144],"proposed":[106],"significantly":[108],"boosts":[109],"distilled":[110],"quality,":[111],"achieving":[112],"up":[113],"5.2":[116],"percentage":[117],"points":[118],"accuracy":[119],"increase":[120],"even":[121],"with":[122],"substantial":[123],"pruning,":[125],"i.e.,":[126],"removing":[127],"80%":[128],"original":[131],"Overall,":[136],"experimental":[138],"results":[139],"highlight":[140],"advantages":[142],"easy-sample":[145],"prioritization":[146],"robustness,":[149],"paving":[150],"way":[152],"more":[154],"effective":[155],"high-quality":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}