{"id":"https://openalex.org/W4415795397","doi":"https://doi.org/10.52202/079017-3841","title":"Towards a Scalable Reference-Free Evaluation of Generative Models","display_name":"Towards a Scalable Reference-Free Evaluation of Generative Models","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4415795397","doi":"https://doi.org/10.52202/079017-3841"},"language":"en","primary_location":{"id":"doi:10.52202/079017-3841","doi":"https://doi.org/10.52202/079017-3841","is_oa":false,"landing_page_url":"https://doi.org/10.52202/079017-3841","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Neural Information Processing Systems 37","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.02961","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114188122","display_name":"Azim Ospanov","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Azim Ospanov","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434263","display_name":"Jingwei Zhang","orcid":"https://orcid.org/0000-0002-1681-6608","observed_orcids":["https://orcid.org/0000-0002-1681-6608","https://orcid.org/0009-0006-3709-7565","https://orcid.org/0000-0003-1770-3776"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingwei Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Mohammad Jalali","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammad Jalali","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088299501","display_name":"Xuenan Cao","orcid":"https://orcid.org/0000-0001-7830-8708","observed_orcids":["https://orcid.org/0000-0001-7830-8708"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuenan Cao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091529166","display_name":"Andrej Bogdanov","orcid":"https://orcid.org/0000-0002-0338-6151","observed_orcids":["https://orcid.org/0000-0002-0338-6151"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrej Bogdanov","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017160178","display_name":"Farzan Farnia","orcid":"https://orcid.org/0000-0002-6049-9232","observed_orcids":["https://orcid.org/0000-0002-6049-9232"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Farzan Farnia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4142,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7053783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"120892","last_page":"120927"},"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":0.6079000234603882,"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":0.6079000234603882,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.16269999742507935,"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/T10028","display_name":"Topic Modeling","score":0.023099999874830246,"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/generative-models","display_name":"generative models","score":0.8220000267028809},{"id":"https://openalex.org/keywords/reference-free-evaluation","display_name":"reference-free evaluation","score":0.8539999723434448},{"id":"https://openalex.org/keywords/scalability","display_name":"scalability","score":0.5490000247955322},{"id":"https://openalex.org/keywords/model-evaluation","display_name":"model evaluation","score":0.4020000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470999717712402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5213000178337097},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31520000100135803},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.28189998865127563},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2689000070095062},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.52202/079017-3841","doi":"https://doi.org/10.52202/079017-3841","is_oa":false,"landing_page_url":"https://doi.org/10.52202/079017-3841","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Neural Information Processing Systems 37","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2407.02961","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.02961","pdf_url":"https://arxiv.org/pdf/2407.02961","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.02961","doi":"https://doi.org/10.48550/arxiv.2407.02961","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.02961","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.02961","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.02961","pdf_url":"https://arxiv.org/pdf/2407.02961","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415795397.pdf","grobid_xml":"https://content.openalex.org/works/W4415795397.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4404341063","https://openalex.org/W4392271053","https://openalex.org/W7172445309","https://openalex.org/W7129474564","https://openalex.org/W7160879804","https://openalex.org/W2946177884","https://openalex.org/W4394862615","https://openalex.org/W4413146007","https://openalex.org/W7133227015","https://openalex.org/W7112394528"],"abstract_inverted_index":{"While":[0],"standard":[1,152],"evaluation":[2],"scores":[3,49],"for":[4,57],"generative":[5,14,59,170],"models":[6,15],"are":[7],"mostly":[8],"reference-based,":[9],"a":[10,125,134],"reference-dependent":[11],"assessment":[12,131],"of":[13,24,43,90,106,120,128],"could":[16],"be":[17],"generally":[18],"difficult":[19],"due":[20],"to":[21,39,53,71,94,110,151,168],"the":[22,29,41,66,73,78,91,97,104,112,118,129,162],"unavailability":[23],"applicable":[25],"reference":[26],"datasets.":[27,157],"Recently,":[28],"reference-free":[30],"entropy":[31,99],"scores,":[32],"VENDI":[33],"and":[34,76,155,165],"RKE,":[35],"have":[36],"been":[37],"proposed":[38],"evaluate":[40,145],"diversity":[42,119],"generated":[44],"data.":[45],"However,":[46],"estimating":[47],"these":[48],"from":[50],"data":[51],"leads":[52],"significant":[54],"computational":[55,74],"costs":[56],"large-scale":[58,169],"models.":[60,171],"In":[61],"this":[62],"work,":[63],"we":[64,102],"leverage":[65],"random":[67],"Fourier":[68],"features":[69],"framework":[70],"reduce":[72],"price":[75],"propose":[77],"Fourier-based":[79],"Kernel":[80],"Entropy":[81],"Approximation":[82],"(FKEA)":[83],"method.":[84],"We":[85,123,143],"utilize":[86],"FKEA's":[87,107,146],"approximated":[88],"eigenspectrum":[89],"kernel":[92],"matrix":[93],"efficiently":[95],"estimate":[96],"mentioned":[98],"scores.":[100],"Furthermore,":[101],"show":[103],"application":[105,150],"proxy":[108],"eigenvectors":[109],"reveal":[111],"method's":[113,163],"identified":[114],"modes":[115],"in":[116,149],"evaluating":[117],"produced":[121],"samples.":[122],"provide":[124],"stochastic":[126],"implementation":[127],"FKEA":[130],"algorithm":[132],"with":[133,139],"complexity":[135],"$O(n)$":[136],"linearly":[137],"growing":[138],"sample":[140],"size":[141],"$n$.":[142],"extensively":[144],"numerical":[147],"performance":[148],"image,":[153],"text,":[154],"video":[156],"Our":[158],"empirical":[159],"results":[160],"indicate":[161],"scalability":[164],"interpretability":[166],"applied":[167],"The":[172],"codebase":[173],"is":[174],"available":[175],"at":[176],"https://github.com/aziksh-ospanov/FKEA.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-11-03T00:00:00"}