{"id":"https://openalex.org/W4415708832","doi":"https://doi.org/10.1109/icme59968.2025.11209069","title":"Enhancing Diffusion-based Dataset Distillation via Adversary-Guided Curriculum Sampling","display_name":"Enhancing Diffusion-based Dataset Distillation via Adversary-Guided Curriculum Sampling","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708832","doi":"https://doi.org/10.1109/icme59968.2025.11209069"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209069","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 Multimedia and Expo (ICME)","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/A5101257950","display_name":"Lexiao Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lexiao Zou","raw_affiliation_strings":["Harbin Institute of Technology,Shenzhen"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007109976","display_name":"Gongwei Chen","orcid":"https://orcid.org/0000-0002-0634-6075"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongwei Chen","raw_affiliation_strings":["Harbin Institute of Technology,Shenzhen"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089966825","display_name":"Yanda Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanda Chen","raw_affiliation_strings":["Harbin Institute of Technology,Shenzhen"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100376455","display_name":"Miao Zhang","orcid":"https://orcid.org/0009-0007-6145-8049"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Zhang","raw_affiliation_strings":["Harbin Institute of Technology,Shenzhen"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Shenzhen","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101257950"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":1.1366,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83789552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.8094000220298767,"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":0.8094000220298767,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.01640000008046627,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.014800000004470348,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.8190000057220459},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6018000245094299},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.49639999866485596},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4666000008583069},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4138999879360199},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3752000033855438}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8190000057220459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7504000067710876},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6018000245094299},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5098000168800354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5016000270843506},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.49639999866485596},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4666000008583069},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4081000089645386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209069","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2296073425","https://openalex.org/W4312252393","https://openalex.org/W4312412605","https://openalex.org/W4312705932","https://openalex.org/W4319300193","https://openalex.org/W4385801729","https://openalex.org/W4386072234","https://openalex.org/W4386075990","https://openalex.org/W4390872297","https://openalex.org/W4390873784","https://openalex.org/W4402727287","https://openalex.org/W4402772294","https://openalex.org/W4411948547"],"related_works":[],"abstract_inverted_index":{"Dataset":[0],"distillation":[1],"aims":[2],"to":[3,51,78,123,159],"encapsulate":[4],"the":[5,22,42,104,146,150,175,192],"rich":[6],"information":[7,79,133],"contained":[8],"in":[9,54],"dataset":[10,15,106],"into":[11,107],"a":[12,89,125,139],"compact":[13],"distilled":[14,90,105,142],"but":[16],"it":[17],"faces":[18],"performance":[19],"degradation":[20],"as":[21,88,145],"image-per-class":[23],"(IPC)":[24],"setting":[25],"or":[26],"image":[27],"resolution":[28],"grows":[29],"larger.":[30],"Recent":[31],"advancements":[32],"demonstrate":[33,174],"that":[34],"integrating":[35],"diffusion":[36,66,116],"generative":[37],"models":[38,67],"can":[39],"effectively":[40],"facilitate":[41],"compression":[43],"of":[44,73,152,167,177,183],"large-scale":[45],"datasets":[46],"while":[47],"maintaining":[48],"efficiency":[49],"due":[50],"their":[52],"superiority":[53],"matching":[55],"data":[56,169],"distribution":[57],"and":[58,137,164,187],"summarizing":[59],"representative":[60],"patterns.":[61],"However,":[62],"images":[63,85,156],"sampled":[64,84,129],"from":[65,157],"are":[68,86],"always":[69],"blamed":[70],"for":[71],"lack":[72],"diversity":[74],"which":[75,102,179],"may":[76],"lead":[77],"redundancy":[80],"when":[81],"multiple":[82,108],"independent":[83],"aggregated":[87],"dataset.":[91,143],"To":[92],"address":[93],"this":[94],"issue,":[95],"we":[96],"propose":[97],"Adversary-guided":[98],"Curriculum":[99],"Sampling":[100],"(ACS),":[101],"partitions":[103],"curricula.":[109],"For":[110],"generating":[111],"each":[112],"curriculum,":[113],"ACS":[114,154],"guides":[115],"sampling":[117],"process":[118],"by":[119],"an":[120],"adversarial":[121],"loss":[122],"challenge":[124],"discriminator":[126,147],"trained":[127],"on":[128,185,189],"images,":[130],"thus":[131],"mitigating":[132],"overlap":[134],"between":[135],"curricula":[136],"fostering":[138],"more":[140,160],"diverse":[141],"Additionally,":[144],"evolves":[148],"with":[149],"progression":[151],"curricula,":[153],"generates":[155],"simpler":[158],"complex,":[161],"ensuring":[162],"efficient":[163],"systematic":[165],"coverage":[166],"target":[168],"informational":[170],"spectrum.":[171],"Extensive":[172],"experiments":[173],"effectiveness":[176],"ACS,":[178],"achieves":[180],"substantial":[181],"improvements":[182],"4.1%":[184],"Imagewoof":[186],"2.1%":[188],"ImageNet-1k":[190],"over":[191],"state-of-the-art.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-30T00:00:00"}
