{"id":"https://openalex.org/W7166716135","doi":"https://doi.org/10.48550/arxiv.2606.28368","title":"EvoRec: Self Evolving Agentic Recommender Systems","display_name":"EvoRec: Self Evolving Agentic Recommender Systems","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7166716135","doi":"https://doi.org/10.48550/arxiv.2606.28368"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.28368","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28368","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.2606.28368","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130577360","display_name":"Lingyu Mu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mu, Lingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139644537","display_name":"Hao Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139671426","display_name":"Haibo Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Haibo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139680800","display_name":"Jinxin Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Jinxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139665792","display_name":"Yu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139666134","display_name":"Xiaoyi Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Xiaoyi","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/T10203","display_name":"Recommender Systems and Techniques","score":0.8838000297546387,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.8838000297546387,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.01600000075995922,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.014800000004470348,"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/recommender-system","display_name":"Recommender system","score":0.7432000041007996},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5788999795913696},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.44929999113082886},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.4146000146865845},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.382099986076355},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.37130001187324524},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.3409000039100647},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.33550000190734863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483999729156494},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7432000041007996},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5788999795913696},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.4146000146865845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3917999863624573},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3472999930381775},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C2776299755","wikidata":"https://www.wikidata.org/wiki/Q432449","display_name":"Carry (investment)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2809000015258789},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.28368","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28368","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.2606.28368","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28368","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":0.5496727228164673,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Optimizing":[0],"modern":[1],"recommender":[2],"systems":[3],"still":[4],"relies":[5],"heavily":[6],"on":[7,121],"engineers":[8],"iterating":[9],"by":[10,17,136],"hand,":[11],"which":[12],"is":[13,36,53],"slow":[14],"and":[15,43,59,80,97,125,144,154],"bounded":[16],"individual":[18],"expertise.":[19],"LLM-based":[20],"agents":[21,88],"open":[22],"a":[23,40,56,72,91,114,150,155],"path":[24],"toward":[25],"automating":[26],"this":[27],"loop,":[28],"yet":[29],"two":[30,122],"issues":[31],"remain.":[32],"First,":[33],"the":[34,50,77,81,94,101,106,141],"agent":[35],"used":[37],"only":[38],"as":[39],"code":[41],"translator":[42],"accumulates":[44],"no":[45],"methodology":[46,83,112],"across":[47],"iterations.":[48],"Second,":[49],"optimization":[51,82],"space":[52],"confined":[54],"to":[55,138],"predefined":[57],"range":[58],"rarely":[60],"introduces":[61],"structurally":[62],"new":[63],"ideas.":[64],"To":[65],"address":[66],"these":[67],"problems,":[68],"we":[69],"propose":[70],"EvoRec,":[71],"multi-agent":[73],"framework":[74],"that":[75,131],"co-evolves":[76],"recommendation":[78],"model":[79,102],"driving":[84],"it.":[85],"Four":[86],"collaborating":[87],"carry":[89],"out":[90],"dual-track":[92],"loop:":[93],"Research":[95],"Agent":[96,99],"Code":[98],"iterate":[100],"each":[103],"round,":[104],"while":[105],"Skill":[107],"Evolver":[108],"periodically":[109],"distills":[110],"reusable":[111],"from":[113],"persistent":[115],"Memory":[116],"of":[117],"past":[118],"experiments.":[119],"Experiments":[120],"public":[123],"benchmarks":[124],"one":[126],"large-scale":[127],"industrial":[128],"dataset":[129],"show":[130],"EvoRec":[132],"improves":[133],"offline":[134],"metrics":[135],"up":[137],"5.54%":[139],"over":[140],"strongest":[142],"baseline,":[143],"an":[145],"online":[146],"A/B":[147],"test":[148],"delivers":[149],"1.85%":[151],"revenue":[152],"lift":[153],"1.02%":[156],"CTR":[157],"gain.":[158]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}