{"id":"https://openalex.org/W7155019002","doi":"https://doi.org/10.48550/arxiv.2604.15877","title":"Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents","display_name":"Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7155019002","doi":"https://doi.org/10.48550/arxiv.2604.15877"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15877","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15877","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.2604.15877","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134068806","display_name":"Xing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134014272","display_name":"Guanghui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guanghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134086929","display_name":"Yanwei Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Yanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134047876","display_name":"Wei Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104473714","display_name":"Ziyuan Li","orcid":"https://orcid.org/0009-0001-1835-3336"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ziyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134058465","display_name":"Bing Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Bing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041585806","display_name":"Peiyang He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Peiyang","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/T12761","display_name":"Data Stream Mining Techniques","score":0.051100000739097595,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.051100000739097595,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.04340000078082085,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.040800001472234726,"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/context","display_name":"Context (archaeology)","score":0.5695000290870667},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5619000196456909},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.41190001368522644},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.3937000036239624},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.39320001006126404},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.3621000051498413},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3546000123023987}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777899980545044},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5695000290870667},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4343999922275543},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37380000948905945},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.3621000051498413},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31790000200271606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30649998784065247},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.3050999939441681},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2847999930381775},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.26420000195503235},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25290000438690186},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15877","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15877","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.2604.15877","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15877","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":[{"score":0.5554142594337463,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"LLM":[1],"agents":[2],"scale":[3],"to":[4,148],"long-horizon,":[5],"multi-session":[6],"deployments,":[7],"efficiently":[8],"managing":[9],"accumulated":[10],"experience":[11],"becomes":[12],"a":[13,34,45,57,69,108,118],"critical":[14],"bottleneck.":[15],"Agent":[16],"memory":[17],"systems":[18,98],"and":[19,64,93,161,173],"agent":[20,179],"skill":[21],"discovery":[22],"both":[23],"address":[24],"this":[25,100],"challenge,":[26],"extracting":[27],"reusable":[28],"knowledge":[29,163],"from":[30],"interaction":[31],"traces,":[32],"yet":[33],"citation":[35,47],"analysis":[36],"of":[37,72,159],"1{,}136":[38],"references":[39],"across":[40],"22":[41],"primary":[42],"papers":[43],"reveals":[44,102],"cross-community":[46],"rate":[48],"below":[49],"1\\%.":[50],"We":[51,125,169],"propose":[52],"the":[53,122,157],"\\emph{Experience":[54],"Compression":[55],"Spectrum},":[56],"unifying":[58],"framework":[59],"that":[60,103,128,142,151,162],"positions":[61],"memory,":[62,78],"skills,":[63,82],"rules":[65],"as":[66],"points":[67],"along":[68],"single":[70],"axis":[71],"increasing":[73],"compression":[74,111,149,155],"(5--20$\\times$":[75],"for":[76,80,84,176],"episodic":[77],"50--500$\\times$":[79],"procedural":[81],"1{,}000$\\times$+":[83],"declarative":[85],"rules),":[86],"directly":[87],"reducing":[88],"context":[89],"consumption,":[90],"retrieval":[91],"latency,":[92],"compute":[94],"overhead.":[95],"Mapping":[96],"20+":[97],"onto":[99],"spectrum":[101],"every":[104],"system":[105],"operates":[106],"at":[107,156],"fixed,":[109],"predetermined":[110],"level:":[112],"none":[113],"supports":[114],"adaptive":[115],"cross-level":[116],"compression,":[117],"gap":[119],"we":[120],"term":[121],"\\emph{missing":[123],"diagonal}.":[124],"further":[126],"show":[127],"specialization":[129],"alone":[130],"is":[131],"insufficient":[132],"(both":[133],"communities":[134],"independently":[135],"solve":[136],"shared":[137],"sub-problems":[138],"without":[139],"exchanging":[140],"solutions),":[141],"evaluation":[143],"methods":[144],"are":[145],"tightly":[146],"coupled":[147],"levels,":[150],"transferability":[152],"increases":[153],"with":[154],"cost":[158],"specificity,":[160],"lifecycle":[164],"management":[165],"remains":[166],"largely":[167],"neglected.":[168],"articulate":[170],"open":[171],"problems":[172],"design":[174],"principles":[175],"scalable,":[177],"full-spectrum":[178],"learning":[180],"systems.":[181]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-21T00:00:00"}