{"id":"https://openalex.org/W7167268862","doi":"https://doi.org/10.48550/arxiv.2607.01237","title":"KARA: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression","display_name":"KARA: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7167268862","doi":"https://doi.org/10.48550/arxiv.2607.01237"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.01237","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01237","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,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.01237","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004937323","display_name":"Shen Han","orcid":"https://orcid.org/0000-0003-0426-8453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Shen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140006384","display_name":"Yuyang Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yuyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yu, Junpu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Junpu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Isayev, Olexandr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Isayev, Olexandr","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":0.3296999931335449,"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":0.3296999931335449,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.06539999693632126,"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/T10933","display_name":"Real-Time Systems Scheduling","score":0.06120000034570694,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.7947999835014343},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5605000257492065},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.558899998664856},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.505299985408783},{"id":"https://openalex.org/keywords/cache-algorithms","display_name":"Cache algorithms","score":0.4927999973297119},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4661000072956085},{"id":"https://openalex.org/keywords/cpu-cache","display_name":"CPU cache","score":0.45019999146461487},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.44749999046325684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8500000238418579},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7947999835014343},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5605000257492065},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.558899998664856},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C38556500","wikidata":"https://www.wikidata.org/wiki/Q13404475","display_name":"Cache algorithms","level":4,"score":0.4927999973297119},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4661000072956085},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.45649999380111694},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.45019999146461487},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.42309999465942383},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3547999858856201},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3467999994754791},{"id":"https://openalex.org/C113166858","wikidata":"https://www.wikidata.org/wiki/Q5015981","display_name":"Cache pollution","level":5,"score":0.3400999903678894},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3118000030517578},{"id":"https://openalex.org/C201148951","wikidata":"https://www.wikidata.org/wiki/Q5015976","display_name":"Cache coloring","level":4,"score":0.30230000615119934},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.2989000082015991},{"id":"https://openalex.org/C25536678","wikidata":"https://www.wikidata.org/wiki/Q5015977","display_name":"Cache invalidation","level":5,"score":0.2904999852180481},{"id":"https://openalex.org/C167713795","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"Smart Cache","level":5,"score":0.26669999957084656},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.01237","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01237","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,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.01237","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01237","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,"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"},"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":{"Reasoning":[0],"language":[1],"models":[2],"often":[3],"generate":[4],"long":[5],"chain-of-thought":[6],"(CoT),":[7],"which":[8,199],"accumulates":[9],"a":[10,36,129,171,176],"massive":[11],"KV":[12,30,47,64,86,104,131,156,180,201],"cache":[13,31,65,132,202],"during":[14],"the":[15,92,143,159],"decoding":[16,21],"phase":[17],"and":[18,23,82,153,190,205,219],"incurs":[19],"high":[20],"latency":[22],"limited":[24,75],"throughput.":[25,209],"To":[26,122,161],"address":[27],"these":[28,124],"issues,":[29],"compression":[32,66,71,133,138],"has":[33],"emerged":[34],"as":[35],"promising":[37],"technique":[38],"for":[39,53],"reducing":[40],"memory":[41,203],"overhead":[42],"by":[43,139],"selectively":[44],"removing":[45],"unimportant":[46],"pairs":[48,87,105,157,181],"while":[49],"preserving":[50],"useful":[51],"ones":[52],"subsequent":[54],"decoding.":[55],"Nevertheless,":[56],"we":[57,126,169,185],"identify":[58],"two":[59],"key":[60],"limitations":[61],"in":[62,158],"existing":[63],"methods:":[67],"1)":[68],"their":[69],"threshold-triggered":[70],"policy":[72],"may":[73,83],"provide":[74],"throughput":[76],"improvement":[77],"or":[78,106],"even":[79],"reduce":[80],"throughput,":[81],"fully":[84],"eliminate":[85],"from":[88],"certain":[89],"blocks":[90],"of":[91,165,178,216],"sequence,":[93],"potentially":[94],"worsening":[95],"information":[96],"loss.":[97],"2)":[98],"they":[99],"typically":[100],"retain":[101],"either":[102],"isolated":[103],"fixed-size":[107],"chunks":[108,117],"with":[109],"rigid":[110],"boundaries,":[111],"failing":[112],"to":[113,151,174,188],"preserve":[114],"important":[115,166],"flexible-sized":[116],"at":[118],"arbitrary":[119],"token":[120],"positions.":[121],"overcome":[123],"limitations,":[125],"propose":[127],"Kara,":[128],"sliding-window":[130],"method":[134],"that":[135],"performs":[136],"decoding-time":[137],"operating":[140],"only":[141],"on":[142],"recently":[144],"generated":[145],"context.":[146],"Kara":[147,187,218],"leverages":[148],"bidirectional":[149],"attention":[150],"score":[152],"select":[154],"informative":[155],"window.":[160],"enable":[162],"flexible":[163],"preservation":[164],"semantic":[167],"information,":[168],"design":[170],"Token2Chunk":[172],"module":[173],"expand":[175],"subset":[177],"selected":[179],"into":[182],"chunks.":[183],"Furthermore,":[184],"adapt":[186],"PagedAttention":[189],"develop":[191],"KvLLM,":[192],"an":[193],"inference":[194],"framework":[195],"built":[196],"upon":[197],"vLLM,":[198],"reduces":[200],"usage":[204],"effectively":[206],"improves":[207],"output":[208],"Extensive":[210],"experiments":[211],"demonstrate":[212],"consistent":[213],"performance":[214],"improvements":[215],"proposed":[217],"KvLLM.":[220]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-04T00:00:00"}