{"id":"https://openalex.org/W7135209323","doi":"https://doi.org/10.48550/arxiv.2603.11564","title":"Where Matters More Than What: Decoding-aligned KV Cache Compression via Position-aware Pseudo Queries","display_name":"Where Matters More Than What: Decoding-aligned KV Cache Compression via Position-aware Pseudo Queries","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135209323","doi":"https://doi.org/10.48550/arxiv.2603.11564"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11564","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025685427","display_name":"Zhenxu Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tian, Zhenxu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128938384","display_name":"Yi Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su, Yi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129030935","display_name":"Juntao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Juntao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129088681","display_name":"Min Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Min","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5025685427"],"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/T10181","display_name":"Natural Language Processing Techniques","score":0.23319999873638153,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.23319999873638153,"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/T10028","display_name":"Topic Modeling","score":0.10440000146627426,"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/T14347","display_name":"Big Data and Digital Economy","score":0.09019999951124191,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7850000262260437},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5982000231742859},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5769000053405762},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5485000014305115},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5016999840736389},{"id":"https://openalex.org/keywords/cache-algorithms","display_name":"Cache algorithms","score":0.47839999198913574},{"id":"https://openalex.org/keywords/cache-pollution","display_name":"Cache pollution","score":0.4162999987602234},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41620001196861267}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8672000169754028},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.7850000262260437},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5982000231742859},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5769000053405762},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C38556500","wikidata":"https://www.wikidata.org/wiki/Q13404475","display_name":"Cache algorithms","level":4,"score":0.47839999198913574},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4172999858856201},{"id":"https://openalex.org/C113166858","wikidata":"https://www.wikidata.org/wiki/Q5015981","display_name":"Cache pollution","level":5,"score":0.4162999987602234},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C201148951","wikidata":"https://www.wikidata.org/wiki/Q5015976","display_name":"Cache coloring","level":4,"score":0.4065000116825104},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.3921999931335449},{"id":"https://openalex.org/C25536678","wikidata":"https://www.wikidata.org/wiki/Q5015977","display_name":"Cache invalidation","level":5,"score":0.382099986076355},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3212999999523163},{"id":"https://openalex.org/C36340418","wikidata":"https://www.wikidata.org/wiki/Q7124288","display_name":"Page cache","level":5,"score":0.3181999921798706},{"id":"https://openalex.org/C167713795","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"Smart Cache","level":5,"score":0.3010999858379364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2809999883174896},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26570001244544983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11564","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":"doi:10.48550/arxiv.2603.11564","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11564","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":"article"},"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],"Key-Value":[1],"(KV)":[2],"cache":[3,20,25,124,199],"is":[4],"crucial":[5],"for":[6,53,153],"efficient":[7],"Large":[8],"Language":[9],"Models":[10],"(LLMs)":[11],"inference,":[12],"but":[13],"excessively":[14],"long":[15],"contexts":[16],"drastically":[17],"increase":[18],"KV":[19,24,123,198],"memory":[21,185],"footprint.":[22],"Existing":[23],"compression":[26,125],"methods":[27],"typically":[28],"rely":[29],"on":[30,194],"input-side":[31],"attention":[32],"patterns":[33],"within":[34],"a":[35,109,131],"prompt":[36],"observation":[37,69,151],"window":[38,70,152],"to":[39,49,76,100,142,189],"estimate":[40],"token":[41,167],"importance":[42,154],"during":[43,94],"the":[44,63,73,81,144,160],"prefill":[45],"stage.":[46],"They":[47],"fail":[48],"preserve":[50],"critical":[51,111],"tokens":[52,80],"future":[54],"generation":[55,82,162],"since":[56],"these":[57],"assessments":[58],"are":[59,91],"not":[60],"derived":[61],"from":[62],"decoding":[64,89],"process.":[65],"Intuitively,":[66],"an":[67,149],"effective":[68,150],"should":[71],"mirror":[72],"decoding-stage":[74],"queries":[75,90,99,129,141],"accurately":[77],"reflect":[78],"which":[79],"process":[83],"will":[84],"attend":[85],"to.":[86],"However,":[87],"ground-truth":[88],"inherently":[92],"unavailable":[93],"inference.":[95],"For":[96],"constructing":[97],"pseudo":[98,128,140],"approximate":[101],"them,":[102],"we":[103,120],"find":[104],"that":[105,137,177],"positional":[106],"information":[107],"plays":[108],"more":[110],"role":[112],"than":[113],"semantic":[114],"content.":[115],"Motivated":[116],"by":[117],"this":[118],"insight,":[119],"propose":[121],"decoding-aligned":[122],"via":[126],"position-aware":[127,139],"(DapQ),":[130],"novel":[132],"and":[133,164,174],"lightweight":[134],"eviction":[135],"framework":[136],"leverages":[138],"simulate":[143],"output":[145],"tokens,":[146],"thereby":[147],"establishing":[148],"assessment.":[155],"It":[156],"aligns":[157],"closely":[158],"with":[159,196],"actual":[161],"context":[163],"enables":[165],"precise":[166],"eviction.":[168],"Extensive":[169],"evaluations":[170],"across":[171],"multiple":[172],"benchmarks":[173],"LLMs":[175],"demonstrate":[176],"DapQ":[178],"achieves":[179],"superior":[180],"performance,":[181],"particularly":[182],"under":[183],"strict":[184],"constraints":[186],"(e.g.,":[187],"up":[188],"nearly":[190],"lossless":[191],"performance":[192],"99.5%":[193],"NIAH":[195],"3%":[197],"budgets).":[200]},"counts_by_year":[],"updated_date":"2026-03-14T06:46:50.379900","created_date":"2026-03-14T00:00:00"}