{"id":"https://openalex.org/W7161811629","doi":"https://doi.org/10.48550/arxiv.2605.19660","title":"OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond","display_name":"OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7161811629","doi":"https://doi.org/10.48550/arxiv.2605.19660"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.19660","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19660","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.19660","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122136707","display_name":"Zunhai Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Zunhai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136594582","display_name":"Rui Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136551912","display_name":"Chao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136606908","display_name":"Yaxiu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yaxiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136604350","display_name":"Yifan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136570667","display_name":"Wei Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136550833","display_name":"Jing Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136572946","display_name":"Dayou Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Dayou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136549789","display_name":"Xialie Zhuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Xialie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136601519","display_name":"Yulei Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Yulei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136602193","display_name":"Yuchen Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yuchen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085964667","display_name":"Yik\u2010Chung Wu","orcid":"https://orcid.org/0000-0002-2738-0387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yik-Chung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136585889","display_name":"Hongxia Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Hongxia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136597758","display_name":"Ngai Wong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Ngai","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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.603600025177002,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.603600025177002,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11478","display_name":"Caching and Content Delivery","score":0.06319999694824219,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.041099999099969864,"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":0.7239000201225281},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5612000226974487},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5264000296592712},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5241000056266785},{"id":"https://openalex.org/keywords/cpu-cache","display_name":"CPU cache","score":0.4650000035762787},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.4618000090122223},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4406000077724457}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7239000201225281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6930999755859375},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5612000226974487},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5264000296592712},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5241000056266785},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4652000069618225},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.4650000035762787},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4530999958515167},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3903999924659729},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30000001192092896},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.2603999972343445}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.19660","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19660","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":"doi:10.48550/arxiv.2605.19660","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19660","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,222],"rapid":[1],"advancement":[2],"toward":[3],"long-context":[4],"reasoning":[5],"and":[6,61,116,127,149,158,172,185,217],"multi-modal":[7],"intelligence":[8],"has":[9],"made":[10],"the":[11,15,27,50,54,72,131,196],"memory":[12,21,213],"footprint":[13,214],"of":[14,53,100],"Key-Value":[16],"(KV)":[17],"cache":[18,119],"a":[19,182,190,204],"dominant":[20],"bottleneck":[22,74],"for":[23,122,224],"efficient":[24],"deployment.":[25],"While":[26],"established":[28],"per-channel":[29,55,132],"quantization":[30,56,76,87,104],"effectively":[31,148],"accommodates":[32],"intrinsic":[33],"channel-wise":[34],"outliers":[35],"in":[36,210],"Key":[37],"tensors,":[38],"its":[39],"efficacy":[40],"diminishes":[41],"under":[42,176],"extreme":[43],"compression.":[44],"In":[45],"this":[46],"work,":[47],"we":[48,108],"revisit":[49],"inherent":[51],"limitations":[52],"paradigm":[57],"from":[58],"both":[59,147],"empirical":[60],"theoretical":[62],"perspectives.":[63],"Our":[64],"analysis":[65],"identifies":[66],"Token":[67],"Norm":[68],"Imbalance":[69],"(TNI)":[70],"as":[71,181],"primary":[73],"to":[75,91,142,207],"fidelity.":[77],"We":[78],"demonstrate":[79],"that":[80,166,188],"TNI":[81],"systematically":[82],"amplifies":[83],"errors":[84],"when":[85],"shared":[86],"parameters":[88],"are":[89],"required":[90],"span":[92],"token":[93],"groups":[94],"exhibiting":[95],"substantial":[96],"norm":[97],"disparities.":[98],"Instead":[99],"relying":[101],"on":[102],"intricate":[103],"pipelines":[105],"(e.g.,":[106],"TurboQuant),":[107],"propose":[109],"OScaR":[110,134,167,201,225],"(Omni-Scaled":[111],"Canalized":[112,136],"Rotation),":[113],"an":[114],"accurate":[115],"lightweight":[117],"KV":[118],"compression":[120],"framework":[121,187],"X-LLMs":[123,164],"(i.e.,":[124],"text-only,":[125],"multi-modal,":[126],"omni-modal":[128],"LLMs).":[129],"Advancing":[130],"paradigm,":[133],"employs":[135],"Rotation":[137],"followed":[138],"by":[139,153,215,220],"Omni-Token":[140],"Scaling":[141],"mitigate":[143],"TNI-induced":[144],"sequence-dimensional":[145],"variance":[146],"efficiently,":[150],"further":[151],"supported":[152],"our":[154,200],"optimized":[155],"system":[156],"design":[157],"CUDA":[159],"kernels.":[160],"Extensive":[161],"evaluations":[162],"across":[163],"show":[165],"consistently":[168],"outperforms":[169],"existing":[170],"methods":[171],"achieves":[173,203],"near-lossless":[174],"performance":[175],"INT2":[177],"quantization,":[178],"establishing":[179],"it":[180],"robust,":[183],"low-complexity,":[184],"universal":[186],"defines":[189],"new":[191],"Pareto":[192],"front.":[193],"Compared":[194],"with":[195],"BF16":[197],"FlashDecoding-v2":[198],"baseline,":[199],"implementation":[202],"notable":[205],"up":[206],"3.0x":[208],"speedup":[209],"decoding,":[211],"reduces":[212],"5.3x,":[216],"increases":[218],"throughput":[219],"4.1x.":[221],"code":[223],"is":[226],"publicly":[227],"available":[228],"at":[229],"https://github.com/ZunhaiSu/OScaR-KV-Quant.":[230]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-21T00:00:00"}