{"id":"https://openalex.org/W4312107722","doi":"https://doi.org/10.48550/arxiv.2212.10878","title":"Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization","display_name":"Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization","publication_year":2022,"publication_date":"2022-12-21","ids":{"openalex":"https://openalex.org/W4312107722","doi":"https://doi.org/10.48550/arxiv.2212.10878"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2212.10878","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.10878","pdf_url":"https://arxiv.org/pdf/2212.10878","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2212.10878","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100762910","display_name":"Seongmin Park","orcid":"https://orcid.org/0000-0003-4172-821X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Park, Seongmin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015122589","display_name":"Beomseok Kwon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwon, Beomseok","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068625256","display_name":"Jieun Lim","orcid":"https://orcid.org/0000-0002-8985-1957"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lim, Jieun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043025566","display_name":"Kyuyoung Sim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sim, Kyuyoung","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100452223","display_name":"Taeho Kim","orcid":"https://orcid.org/0000-0003-4522-5388"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Tae-Ho","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089720016","display_name":"Jungwook Choi","orcid":"https://orcid.org/0000-0001-5916-9714"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Jungwook","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100762910"],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9896000027656555,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9861000180244446,"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":0.8953651189804077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7108827829360962},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.6347049474716187},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.572867214679718},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5574526786804199},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5180911421775818},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.38797155022621155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30076783895492554},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.150638610124588}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.8953651189804077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7108827829360962},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.6347049474716187},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.572867214679718},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5574526786804199},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5180911421775818},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.38797155022621155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30076783895492554},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.150638610124588}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2212.10878","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.10878","pdf_url":"https://arxiv.org/pdf/2212.10878","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2212.10878","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2212.10878","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2212.10878","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2212.10878","pdf_url":"https://arxiv.org/pdf/2212.10878","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4315697128","https://openalex.org/W4382323155","https://openalex.org/W3205506801","https://openalex.org/W4292794827","https://openalex.org/W4224939635","https://openalex.org/W3204400881","https://openalex.org/W3183118997","https://openalex.org/W3214410901","https://openalex.org/W3204296682","https://openalex.org/W2917767146"],"abstract_inverted_index":{"Uniform-precision":[0],"neural":[1,42,46],"network":[2,52],"quantization":[3,27,70,102],"has":[4],"gained":[5],"popularity":[6],"since":[7],"it":[8,19],"simplifies":[9],"densely":[10],"packed":[11],"arithmetic":[12],"unit":[13],"for":[14,68,116],"high":[15],"computing":[16],"capability.":[17],"However,":[18],"ignores":[20],"heterogeneous":[21],"sensitivity":[22],"to":[23,54,98],"the":[24,30,51,69,89,112,123],"impact":[25],"of":[26],"errors":[28],"across":[29],"layers,":[31],"resulting":[32],"in":[33],"sub-optimal":[34],"inference":[35],"accuracy.":[36],"This":[37],"work":[38],"proposes":[39],"a":[40],"novel":[41],"architecture":[43],"search":[44],"called":[45],"channel":[47],"expansion":[48],"that":[49,88],"adjusts":[50],"structure":[53],"alleviate":[55],"accuracy":[56,103,115],"degradation":[57],"from":[58],"ultra-low":[59],"uniform-precision":[60],"quantization.":[61],"The":[62],"proposed":[63,90],"method":[64,91],"selectively":[65],"expands":[66],"channels":[67,97],"sensitive":[71],"layers":[72],"while":[73],"satisfying":[74],"hardware":[75],"constraints":[76],"(e.g.,":[77],"FLOPs,":[78],"PARAMs).":[79],"Based":[80],"on":[81,104],"in-depth":[82],"analysis":[83],"and":[84,106,122],"experiments,":[85],"we":[86,110],"demonstrate":[87],"can":[92],"adapt":[93],"several":[94],"popular":[95],"networks":[96],"achieve":[99,111],"superior":[100],"2-bit":[101,117],"CIFAR10":[105],"ImageNet.":[107],"In":[108],"particular,":[109],"best-to-date":[113],"Top-1/Top-5":[114],"ResNet50":[118],"with":[119],"smaller":[120],"FLOPs":[121],"parameter":[124],"size.":[125]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2023-01-04T00:00:00"}