{"id":"https://openalex.org/W7134069327","doi":"https://doi.org/10.3233/faia260019","title":"LLMs in the Loop: From Ratings to Ranked Recommendations","display_name":"LLMs in the Loop: From Ratings to Ranked Recommendations","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7134069327","doi":"https://doi.org/10.3233/faia260019"},"language":null,"primary_location":{"id":"doi:10.3233/faia260019","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia260019","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/faia260019","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059512798","display_name":"Ethan Low","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ethan Low","raw_affiliation_strings":["Computer Science Dept., Brigham Young Univ., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Brigham Young Univ., USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086456104","display_name":"Yiu\u2010Kai Ng","orcid":"https://orcid.org/0000-0002-5680-2796"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiu-Kai Ng","raw_affiliation_strings":["Computer Science Dept., Brigham Young Univ., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Dept., Brigham Young Univ., USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059512798"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46116838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.5982999801635742,"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":0.5982999801635742,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.08619999885559082,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.032499998807907104,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7157999873161316},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6843000054359436},{"id":"https://openalex.org/keywords/rating-system","display_name":"Rating system","score":0.6650000214576721},{"id":"https://openalex.org/keywords/large-sample","display_name":"Large sample","score":0.3716000020503998},{"id":"https://openalex.org/keywords/rating-scale","display_name":"Rating scale","score":0.3472999930381775},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.2921999990940094}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7157999873161316},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6843000054359436},{"id":"https://openalex.org/C2988118254","wikidata":"https://www.wikidata.org/wiki/Q16881889","display_name":"Rating system","level":2,"score":0.6650000214576721},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.37389999628067017},{"id":"https://openalex.org/C3020318244","wikidata":"https://www.wikidata.org/wiki/Q4812187","display_name":"Large sample","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3517000079154968},{"id":"https://openalex.org/C83849319","wikidata":"https://www.wikidata.org/wiki/Q7295720","display_name":"Rating scale","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.2971000075340271},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia260019","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia260019","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia260019","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia260019","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"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":{"The":[0,65],"advent":[1],"of":[2,57,125],"Large":[3],"Language":[4],"Models":[5],"(LLMs)":[6],"has":[7],"the":[8,55,128,147],"potential":[9],"to":[10,21,99,107,120,168,212],"transform":[11],"item":[12,60,104],"rankings":[13],"and":[14,24,44,63,75,95,103,117,132,161,215],"recommender":[15],"systems":[16],"by":[17],"leveraging":[18],"extensive":[19],"training":[20],"provide":[22],"nuanced":[23],"personalized":[25],"suggestions":[26],"based":[27],"on":[28],"comprehensive":[29],"contextual":[30],"information":[31,173],"about":[32],"items.":[33],"LLMs":[34,58,66,186,199,214],"offer":[35],"advantages,":[36],"such":[37],"as":[38,72,76],"easy":[39],"updating":[40],"with":[41,139,203],"new":[42],"preferences":[43],"flexibility,":[45],"in":[46,69,187,194],"maintaining":[47],"current":[48],"relevance.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53,155],"explore":[54],"use":[56],"for":[59],"rating":[61,73,101,130,165,188],"prediction":[62,131],"recommendation.":[64,134],"were":[67],"tested":[68],"their":[70,108],"capacities":[71],"predictors":[74],"ranked":[77,196],"recommended":[78],"list":[79],"generators.":[80],"We":[81,111],"have":[82,150],"chosen":[83],"four":[84],"advanced":[85],"LLMs,":[86],"Llama":[87,204],"3.1":[88,205],"70B,":[89],"Qwen":[90],"2.5":[91],"32B,":[92],"Mistral":[93],"7B,":[94],"OpenLLaMA":[96],"2.0":[97],"13B":[98],"be":[100],"generators":[102],"recommenders":[105],"due":[106],"transformer-based":[109],"architecture.":[110],"also":[112],"conducted":[113],"an":[114],"n-shot":[115],"experimentation":[116],"fine":[118],"tuning":[119],"assess":[121,169],"how":[122,170],"different":[123],"amounts":[124],"data":[126,141],"influenced":[127],"LLMs\u2019":[129],"ranking":[133],"It":[135],"is":[136],"theorized":[137],"that":[138,179],"more":[140,151],"regarding":[142],"a":[143],"user\u2019s":[144,163],"specific":[145],"tastes":[146],"model":[148],"will":[149],"accurate":[152],"results.":[153],"Specifically,":[154],"evaluated":[156],"three":[157],"sample":[158,172],"sizes\u20145,":[159],"10,":[160],"each":[162],"full":[164],"history\u2014plus":[166],"fine-tuning,":[167],"increased":[171],"affects":[174],"accuracy.":[175,192],"Experimental":[176],"results":[177,210],"showed":[178],"traditional":[180],"User-Based":[181],"Collaborative":[182],"Filtering":[183],"(UBCF)":[184],"outperformed":[185],"prediction,":[189],"yielding":[190],"higher":[191],"However,":[193],"generating":[195],"recommendation":[197],"lists,":[198],"exhibited":[200],"strong":[201],"performance,":[202],"70B":[206],"achieving":[207],"superior":[208],"overall":[209],"compared":[211],"other":[213],"UBCF.":[216]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-03-07T00:00:00"}