{"id":"https://openalex.org/W7128041012","doi":"https://doi.org/10.48550/arxiv.2602.04929","title":"TurboBoA: Faster and Exact Attention-aware Quantization without Backpropagation","display_name":"TurboBoA: Faster and Exact Attention-aware Quantization without Backpropagation","publication_year":2026,"publication_date":"2026-02-04","ids":{"openalex":"https://openalex.org/W7128041012","doi":"https://doi.org/10.48550/arxiv.2602.04929"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.04929","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101941756","display_name":"Junhan Kim","orcid":"https://orcid.org/0000-0001-8960-5425"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Junhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125231142","display_name":"Yeo Jeong Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Yeo Jeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124873902","display_name":"Seungwoo Son","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Son, Seungwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125144595","display_name":"Chungman Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Chungman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100670377","display_name":"Hoyoung Kim","orcid":"https://orcid.org/0000-0003-0476-9020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Ho-young","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125130776","display_name":"Joonyoung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Joonyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112636409","display_name":"Yongkweon Jeon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeon, Yongkweon","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":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":0.5920000076293945,"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":0.5920000076293945,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.07680000364780426,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.042500000447034836,"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":0.7785000205039978},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6434000134468079},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47690001130104065},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.38109999895095825},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.3508000075817108},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.34860000014305115},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.33379998803138733}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7785000205039978},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6434000134468079},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6207000017166138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6108999848365784},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.3271999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30160000920295715},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2858999967575073},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2581999897956848},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.04929","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.04929","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.04929","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.04929","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,107,193],"rapid":[1],"growth":[2],"of":[3,12,47,100,117],"large":[4],"language":[5],"models":[6],"(LLMs)":[7],"has":[8,26],"heightened":[9],"the":[10,97,105],"importance":[11],"post-training":[13],"quantization":[14,75,116],"(PTQ)":[15],"for":[16,30,141],"reducing":[17],"memory":[18],"and":[19,130,148,190],"computation":[20,152],"costs.":[21],"Among":[22],"PTQ":[23,93],"methods,":[24],"GPTQ":[25,62],"gained":[27],"significant":[28],"attention":[29,68],"its":[31,71],"efficiency,":[32],"enabling":[33],"billion-scale":[34],"LLMs":[35],"to":[36,51,157],"be":[37,196],"quantized":[38,146],"within":[39,67],"a":[40,90,121,134,138],"few":[41],"GPU":[42],"hours.":[43],"However,":[44],"GPTQ's":[45],"assumption":[46],"layer-wise":[48],"independence":[49],"leads":[50],"severe":[52],"accuracy":[53,98],"drops":[54],"in":[55,187],"low-bit":[56],"regimes.":[57],"Recently,":[58],"BoA":[59,101,172],"improved":[60],"upon":[61],"by":[63],"incorporating":[64],"inter-layer":[65],"dependencies":[66],"modules,":[69],"but":[70],"reliance":[72],"on":[73],"sequential":[74,128],"across":[76],"all":[77],"out-channels":[78,119],"makes":[79],"it":[80,183],"substantially":[81],"less":[82],"efficient.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87],"propose":[88],"TurboBoA,":[89],"new":[91],"backpropagation-free":[92],"algorithm":[94],"that":[95,166],"preserves":[96],"benefits":[99],"while":[102,173],"significantly":[103],"accelerating":[104],"process.":[106],"proposed":[108],"TurboBoA":[109,167],"introduces":[110],"three":[111],"key":[112],"innovations:":[113],"(i)":[114],"joint":[115],"multiple":[118],"with":[120,153,179],"closed-form":[122],"error":[123],"compensation":[124],"rule,":[125],"which":[126],"reduces":[127],"bottlenecks":[129],"yields":[131],"more":[132],"than":[133],"three-fold":[135],"speedup;":[136],"(ii)":[137],"correction":[139],"mechanism":[140],"errors":[142],"propagated":[143],"from":[144],"preceding":[145],"layers;":[147],"(iii)":[149],"adaptive":[150],"grid":[151],"coordinate":[154],"descent":[155],"refinement":[156],"maintain":[158],"alignment":[159],"during":[160],"iterative":[161],"updates.":[162],"Extensive":[163],"experiments":[164],"demonstrate":[165],"delivers":[168],"substantial":[169],"acceleration":[170],"over":[171],"consistently":[174],"improving":[175],"accuracy.":[176],"When":[177],"combined":[178],"outlier":[180],"suppression":[181],"techniques,":[182],"achieves":[184],"state-of-the-art":[185],"results":[186],"both":[188],"weight-only":[189],"weight-activation":[191],"quantization.":[192],"code":[194],"will":[195],"available":[197],"at":[198],"https://github.com/SamsungLabs/TurboBoA.":[199]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-02-07T00:00:00"}