{"id":"https://openalex.org/W7164134386","doi":"https://doi.org/10.48550/arxiv.2606.09916","title":"IntentKV: Cross-Turn Intent-Aware KV Cache Pruning for Agent Inference","display_name":"IntentKV: Cross-Turn Intent-Aware KV Cache Pruning for Agent Inference","publication_year":2026,"publication_date":"2026-06-06","ids":{"openalex":"https://openalex.org/W7164134386","doi":"https://doi.org/10.48550/arxiv.2606.09916"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09916","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09916","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.2606.09916","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138330588","display_name":"Junjie Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062969662","display_name":"Jiong Lou","orcid":"https://orcid.org/0000-0001-9245-2626"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lou, Jiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138369806","display_name":"Jie Li (15030)","orcid":"https://orcid.org/0009-0007-0165-9068"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jie","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/T12292","display_name":"Graph Theory and Algorithms","score":0.1809999942779541,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.1809999942779541,"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":0.13109999895095825,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.07940000295639038,"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":0.4975000023841858},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.45680001378059387},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.45179998874664307},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42399999499320984},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.39559999108314514},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.3944000005722046},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.3441999852657318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7451000213623047},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5103999972343445},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.4975000023841858},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.45680001378059387},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.34700000286102295},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C2781345722","wikidata":"https://www.wikidata.org/wiki/Q5308388","display_name":"Drop (telecommunication)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.2720000147819519},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.2703000009059906}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09916","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09916","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.2606.09916","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09916","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-turn":[0],"LLM":[1,58],"agents":[2],"fan":[3],"short":[4],"queries":[5,155],"into":[6],"long":[7],"trajectories":[8],"of":[9,27,65],"tool":[10],"calls,":[11],"search":[12],"results,":[13],"and":[14,20,76,112,146,176],"intermediate":[15],"reasoning.":[16],"Both":[17],"KV":[18,21,52,131,136,179],"memory":[19],"read":[22],"bandwidth":[23],"grow":[24],"by":[25],"orders":[26],"magnitude":[28],"across":[29],"a":[30,62,73,78,95,102,173,185],"single":[31],"trajectory,":[32],"making":[33],"the":[34,41,56,120,151],"key-value":[35],"(KV)":[36],"cache,":[37],"not":[38],"parameter":[39],"compute,":[40],"dominant":[42],"serving":[43],"bottleneck":[44],"for":[45],"long-horizon":[46],"agents.":[47],"We":[48],"introduce":[49],"IntentKV,":[50],"learned":[51],"pruning":[53],"that":[54,156],"keeps":[55],"base":[57],"frozen.":[59],"IntentKV":[60,118],"maintains":[61],"session-level":[63],"QueryMemory":[64],"cross-turn":[66],"intent,":[67],"scores":[68],"live":[69],"history":[70],"tokens":[71,141,168],"with":[72,82,90,124],"memory-attention":[74],"rule,":[75],"adds":[77],"zero-initialized":[79],"residual":[80],"head":[81],"cross-attention":[83],"over":[84],"current-query":[85],"K-vectors.":[86],"To":[87],"stay":[88,115],"composable":[89],"prefix":[91],"caches,":[92],"eviction":[93],"is":[94],"slot-map":[96],"redirection:":[97],"dropped":[98],"positions":[99],"route":[100],"to":[101,171,183],"sentinel":[103],"dead":[104],"slot":[105,113],"while":[106],"surviving":[107],"K/V":[108],"rows,":[109],"RoPE":[110],"phases,":[111],"identities":[114],"in":[116],"place.":[117],"matches":[119],"no-pruning":[121],"full-cache":[122],"baseline":[123],"almost":[125],"no":[126],"accuracy":[127],"drop":[128,142],"under":[129],"tight":[130],"budgets:":[132],"at":[133],"an":[134],"8k":[135],"budget,":[137],"mean":[138],"peak":[139,166],"request":[140,167],"23.9%":[143],"on":[144,148,160],"Qwen3-8B":[145],"30.7%":[147],"Qwen2.5-14B.":[149],"On":[150],"100":[152],"longest":[153],"BCP":[154],"all":[157],"methods":[158],"complete":[159],"Qwen2.5-14B,":[161],"IntentKV-8k":[162],"further":[163],"cuts":[164],"worst-case":[165,177],"from":[169,181],"92.3k":[170],"20.5k,":[172],"77.8%":[174],"reduction,":[175],"raw":[178],"reads":[180],"411M":[182],"31M,":[184],"92.6%":[186],"reduction.":[187]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-11T00:00:00"}
