{"id":"https://openalex.org/W7152436307","doi":"https://doi.org/10.48550/arxiv.2604.06746","title":"StructKV: Preserving the Structural Skeleton for Scalable Long-Context Inference","display_name":"StructKV: Preserving the Structural Skeleton for Scalable Long-Context Inference","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152436307","doi":"https://doi.org/10.48550/arxiv.2604.06746"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.06746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06746","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.06746","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133254338","display_name":"Zhirui Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Zhirui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114155627","display_name":"P. Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Peiyang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133243320","display_name":"Ling Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Ling","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5133254338"],"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/T14347","display_name":"Big Data and Digital Economy","score":0.1996999979019165,"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"}},"topics":[{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.1996999979019165,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.15809999406337738,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.05649999901652336,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.6646000146865845},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6215999722480774},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5396999716758728},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.5033000111579895},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4819999933242798},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47999998927116394},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4465000033378601},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4422999918460846},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.41530001163482666}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140000104904175},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.6646000146865845},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6215999722480774},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5396999716758728},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.5033000111579895},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4819999933242798},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.426800012588501},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.39100000262260437},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3889000117778778},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3474999964237213},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34130001068115234},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3271999955177307},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3075000047683716},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.2678999900817871},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.262800008058548},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.06746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06746","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.06746","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06746","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"As":[0],"Large":[1],"Language":[2],"Models":[3],"(LLMs)":[4],"scale":[5],"to":[6,45,119,131],"support":[7],"context":[8],"windows":[9],"exceeding":[10],"one":[11],"million":[12],"tokens,":[13],"the":[14,29,76,84,116,134,145,149,156],"linear":[15],"growth":[16],"of":[17,31],"Key-Value":[18],"(KV)":[19],"cache":[20,100],"imposes":[21],"severe":[22],"memory":[23,150],"capacity":[24],"and":[25,142,158,168],"bandwidth":[26],"bottlenecks,":[27],"constraining":[28],"efficiency":[30],"long-context":[32],"inference.":[33],"Existing":[34],"compression":[35,101],"approaches":[36],"typically":[37],"prioritize":[38],"tokens":[39,68],"based":[40],"on":[41,57,155],"local":[42,58],"saliency":[43,59],"metrics":[44,130],"decouple":[46],"prefill":[47],"computation":[48],"from":[49,148],"decoding":[50],"memory.":[51],"However,":[52],"these":[53],"methods":[54],"often":[55],"rely":[56],"snapshots":[60],"at":[61,83],"a":[62,97],"specific":[63,85],"layer,":[64],"thereby":[65],"systematically":[66],"discarding":[67],"that":[69,103,162],"act":[70],"as":[71],"global":[72,121],"information":[73,122],"hubs":[74],"across":[75,115],"network":[77,117],"depth":[78,118],"but":[79],"appear":[80],"temporarily":[81],"dormant":[82],"layer":[86,136],"selected":[87],"for":[88,137],"pruning.":[89],"To":[90],"address":[91],"this":[92],"limitation,":[93],"we":[94],"propose":[95],"StructKV,":[96],"structure-aware":[98],"KV":[99],"framework":[102],"introduces":[104],"three":[105],"core":[106],"innovations:":[107],"First,":[108],"Global":[109],"In-Degree":[110],"Centrality":[111],"aggregates":[112],"attention":[113],"patterns":[114],"identify":[120],"hubs.":[123],"Second,":[124],"Dynamic":[125],"Pivot":[126],"Detection":[127],"utilizes":[128],"information-theoretic":[129],"adaptively":[132],"locate":[133],"optimal":[135],"compression.":[138],"Finally,":[139],"Structural":[140],"Propagation":[141],"Decoupling":[143],"separates":[144],"computational":[146],"budget":[147],"storage":[151],"budget.":[152],"Experimental":[153],"results":[154],"LongBench":[157],"RULER":[159],"benchmarks":[160],"demonstrate":[161],"StructKV":[163],"effectively":[164],"preserves":[165],"long-range":[166],"dependencies":[167],"retrieval":[169],"robustness.":[170]},"counts_by_year":[],"updated_date":"2026-04-10T06:07:51.998497","created_date":"2026-04-10T00:00:00"}
