{"id":"https://openalex.org/W4408345683","doi":"https://doi.org/10.1109/icassp49660.2025.10888233","title":"PQNAS: Mixed-precision Quantization-aware Neural Architecture Search with Pseudo Quantizer","display_name":"PQNAS: Mixed-precision Quantization-aware Neural Architecture Search with Pseudo Quantizer","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408345683","doi":"https://doi.org/10.1109/icassp49660.2025.10888233"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5108992290","display_name":"Tianxiao Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianxiao Gao","raw_affiliation_strings":["Ant Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100675165","display_name":"Li Guo","orcid":"https://orcid.org/0000-0002-9723-3294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Guo","raw_affiliation_strings":["Ant Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065697745","display_name":"Shihao Wang","orcid":"https://orcid.org/0000-0001-6152-3559"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shihao Wang","raw_affiliation_strings":["Ant Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050416778","display_name":"Shiai Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shiai Zhu","raw_affiliation_strings":["Ant Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108374571","display_name":"Dajiang Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dajiang Zhou","raw_affiliation_strings":["Ant Group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ant Group","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9842000007629395,"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/T10320","display_name":"Neural Networks and Applications","score":0.9842000007629395,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9631999731063843,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9545999765396118,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.7251085042953491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7050981521606445},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.578472375869751},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38696929812431335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3492201566696167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2938602566719055}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7251085042953491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7050981521606445},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.578472375869751},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38696929812431335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3492201566696167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2938602566719055},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2043481157","https://openalex.org/W2108598243","https://openalex.org/W2953604046","https://openalex.org/W2963122961","https://openalex.org/W2963351448","https://openalex.org/W2982083293","https://openalex.org/W2982479999","https://openalex.org/W3035183452","https://openalex.org/W3035332806","https://openalex.org/W3096533519","https://openalex.org/W3108720720","https://openalex.org/W3154998900","https://openalex.org/W3168622113","https://openalex.org/W3204296682","https://openalex.org/W3215340516","https://openalex.org/W4239181501","https://openalex.org/W4386066352","https://openalex.org/W6690026940","https://openalex.org/W6753069482","https://openalex.org/W6754503602","https://openalex.org/W6756979132","https://openalex.org/W6760069825","https://openalex.org/W6767064347","https://openalex.org/W6784847242","https://openalex.org/W6787972765","https://openalex.org/W6795131729","https://openalex.org/W6796873215","https://openalex.org/W6810983866","https://openalex.org/W6846147203"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2038503502"],"abstract_inverted_index":{"Quantization-aware":[0],"neural":[1],"architecture":[2],"search":[3,10],"is":[4,62,83],"an":[5],"efficient":[6],"way":[7],"to":[8,39,64],"automatically":[9],"for":[11,32,77,94,148],"the":[12,19,29,34,66,70,91,132,137,156,159],"best":[13],"quantized":[14,35,71],"model":[15],"that":[16],"can":[17,143],"meet":[18],"limited":[20],"resource":[21],"constraints":[22],"on":[23,167,175],"edge":[24],"devices.":[25],"Existing":[26],"methods":[27],"utilize":[28],"straight-through":[30],"estimator":[31],"training":[33,82],"supernet,":[36],"but":[37],"lead":[38],"oscillation":[40],"problem":[41],"of":[42,60,69,90,99,134],"learned":[43],"weights.":[44],"To":[45,108],"address":[46],"this":[47,109],"issue,":[48],"we":[49,111,142],"introduce":[50],"pseudo":[51,138],"quantization":[52,79,92,125],"noise":[53,76,106,146],"(PQN)":[54],"in":[55,104,136],"quantization-aware":[56,116],"NAS.":[57],"Accurate":[58],"range":[59,147],"PQN":[61],"vital":[63],"ensuring":[65],"high":[67],"accuracy":[68,165],"networks.":[72],"However,":[73],"producing":[74],"accurate":[75,145],"activation":[78,135],"during":[80,151],"supernet":[81],"challenging,":[84],"as":[85],"it":[86],"requires":[87],"precise":[88],"estimation":[89],"parameters":[93,126],"each":[95],"subnet.":[96],"Different":[97],"distributions":[98],"different":[100,105,149],"subnets":[101,150],"will":[102],"result":[103],"range.":[107],"end,":[110],"propose":[112,123],"PQNAS,":[113],"a":[114],"mixed-precision":[115],"NAS":[117],"framework":[118],"with":[119,131,155],"Pseudo":[120],"Quantizer.":[121],"We":[122],"adaptive":[124],"(AQP)":[127],"which":[128],"are":[129],"trained":[130],"distribution":[133],"quantizer.":[139],"With":[140],"AQP,":[141],"obtain":[144],"training.":[152],"Experimentally,":[153],"comparing":[154],"existing":[157],"method,":[158],"proposed":[160],"PQNAS":[161],"achieves":[162],"0.99%\u223c6.48%":[163],"Top-1":[164],"improvement":[166,174],"ImageNet":[168],"1K":[169],"dataset":[170],"and":[171],"1.1%":[172],"mAP":[173],"COCO":[176],"dataset.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}