{"id":"https://openalex.org/W4416252059","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229141","title":"PREF: A Personalized Retrieval-Evolution Framework for Enhancing Large Language Models on General Text Tasks","display_name":"PREF: A Personalized Retrieval-Evolution Framework for Enhancing Large Language Models on General Text Tasks","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416252059","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229141"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113769598","display_name":"Shaoqi Song","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoqi Song","raw_affiliation_strings":["Northwestern Polytechnical University,Department of Computer Science,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,Department of Computer Science,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076603720","display_name":"Lianwei Wu","orcid":"https://orcid.org/0000-0003-1451-9295"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianwei Wu","raw_affiliation_strings":["Northwestern Polytechnical University,Department of Computer Science,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,Department of Computer Science,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085324419","display_name":"Linyong Wang","orcid":"https://orcid.org/0000-0001-5676-0234"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linyong Wang","raw_affiliation_strings":["Northwestern Polytechnical University,Department of Computer Science,Xi’an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University,Department of Computer Science,Xi’an,China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16272566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.3950999975204468,"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/T10028","display_name":"Topic Modeling","score":0.3950999975204468,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.10559999942779541,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.05480000004172325,"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/language-model","display_name":"Language model","score":0.7242000102996826},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.6607000231742859},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6202999949455261},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5321000218391418},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41019999980926514},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.3668999969959259},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.36570000648498535}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8579000234603882},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7242000102996826},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.6607000231742859},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5321000218391418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4975000023841858},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.3668999969959259},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.36570000648498535},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36399999260902405},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3578999936580658},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3086000084877014},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2732999920845032},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.26649999618530273}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2890394457","https://openalex.org/W2963825865","https://openalex.org/W2970909388","https://openalex.org/W3044438666","https://openalex.org/W3090516735","https://openalex.org/W3154903254","https://openalex.org/W3155391257","https://openalex.org/W3156789018","https://openalex.org/W3168255966","https://openalex.org/W3173777717","https://openalex.org/W4205991051","https://openalex.org/W4206732210","https://openalex.org/W4224279631","https://openalex.org/W4283257392","https://openalex.org/W4285135530","https://openalex.org/W4385521210","https://openalex.org/W4385573003","https://openalex.org/W4389520756","https://openalex.org/W4396736493","https://openalex.org/W4402671806"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,55,66,121,146],"maturation":[2],"and":[3,31,49,58,103,138],"advancement":[4],"of":[5,54,60,148],"large":[6,39,149],"language":[7,35,150],"models":[8,36,40,114],"(LLMs),":[9],"personalizing":[10],"content":[11,143],"generation":[12,144],"has":[13],"emerged":[14],"as":[15,83],"a":[16,135],"significant":[17],"challenge.":[18],"Traditional":[19],"approaches":[20],"rely":[21],"on":[22],"retrieving":[23],"historical":[24,75,116],"data":[25,76,117],"from":[26],"users":[27],"with":[28,78,115,125],"similar":[29],"queries":[30],"either":[32],"retraining":[33],"small":[34],"or":[37],"fine-tuning":[38],"for":[41,141],"specific":[42],"tasks,":[43],"both":[44],"requiring":[45],"substantial":[46],"computational":[47,122],"resources":[48],"maintenance.":[50],"To":[51],"take":[52],"advantage":[53],"increasing":[56],"capabilities":[57],"cost-effectiveness":[59],"publicly":[61],"deployed":[62],"LLMs,":[63],"we":[64],"propose":[65],"Personalized":[67],"Retrieval-Evolution":[68],"Framework":[69],"(PREF).":[70],"This":[71],"framework":[72,133],"innovatively":[73],"combines":[74],"retrieval":[77],"cost-effective":[79],"LLM":[80],"API":[81],"calls":[82],"evaluation":[84],"functions":[85],"through":[86],"strategic":[87],"prompt":[88],"reuse.":[89],"Additionally,":[90],"it":[91],"employs":[92],"genetic":[93],"algorithms":[94],"to":[95],"identify":[96],"keywords":[97],"that":[98,110],"best":[99],"characterize":[100],"user":[101],"styles":[102],"characteristics.":[104],"Our":[105],"approach":[106],"surpasses":[107],"conventional":[108],"methods":[109],"combine":[111],"fine-tuned":[112],"smaller":[113],"retrieval,":[118],"while":[119],"eliminating":[120],"overhead":[123],"associated":[124],"repeated":[126],"model":[127],"training":[128],"during":[129],"task":[130],"transitions.":[131],"The":[132],"demonstrates":[134],"more":[136],"efficient":[137],"adaptable":[139],"solution":[140],"personalized":[142],"in":[145],"era":[147],"models.":[151]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-14T00:00:00"}