{"id":"https://openalex.org/W7138403476","doi":"https://doi.org/10.1609/aaai.v40i18.38605","title":"Hard vs. Noise: Resolving Hard-Noisy Sample Confusion in Recommender Systems via Large Language Models","display_name":"Hard vs. Noise: Resolving Hard-Noisy Sample Confusion in Recommender Systems via Large Language Models","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138403476","doi":"https://doi.org/10.1609/aaai.v40i18.38605"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i18.38605","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i18.38605","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38605/42567","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38605/42567","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129726211","display_name":"Tianrui Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tianrui Song","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou)"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102026299","display_name":"Wenshuo Chao","orcid":"https://orcid.org/0009-0002-3640-1087"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen-Shuo Chao","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou)"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129684590","display_name":"Hao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Liu","raw_affiliation_strings":["The Hong Kong University of Science and Technology (Guangzhou)\nThe Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology (Guangzhou)\nThe Hong Kong University of Science and Technology","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5129726211"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70949721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"18","first_page":"15743","last_page":"15751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6944000124931335,"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":0.6944000124931335,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.05779999867081642,"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/T10028","display_name":"Topic Modeling","score":0.04670000076293945,"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/relevance","display_name":"Relevance (law)","score":0.7233999967575073},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6101999878883362},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49149999022483826},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4788999855518341},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4616999924182892},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.454800009727478},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43799999356269836},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.43149998784065247},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4077000021934509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839999794960022},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7233999967575073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6104999780654907},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6101999878883362},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47920000553131104},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4790000021457672},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4788999855518341},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4616999924182892},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.454800009727478},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43799999356269836},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.43149998784065247},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4077000021934509},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3375999927520752},{"id":"https://openalex.org/C75917345","wikidata":"https://www.wikidata.org/wiki/Q2725298","display_name":"Sampling bias","level":3,"score":0.33469998836517334},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25049999356269836},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i18.38605","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i18.38605","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38605/42567","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i18.38605","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i18.38605","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/38605/42567","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138403476.pdf","grobid_xml":"https://content.openalex.org/works/W7138403476.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Implicit":[0],"feedback,":[1],"employed":[2],"in":[3,113],"training":[4],"recommender":[5],"systems,":[6],"unavoidably":[7],"confronts":[8],"noise":[9],"due":[10],"to":[11,23,59,96,116,132,159,206],"factors":[12],"such":[13,32],"as":[14,33,67],"misclicks":[15],"and":[16,37,52,99,162,174,218],"position":[17],"bias.":[18],"Previous":[19],"studies":[20],"have":[21],"attempted":[22],"identify":[24,160],"noisy":[25,50,100,123,163],"samples":[26,51,54,69],"through":[27,41],"their":[28,39],"diverged":[29],"data":[30],"patterns,":[31,57],"higher":[34],"loss":[35],"values,":[36],"mitigate":[38],"influence":[40],"sample":[42],"dropping":[43],"or":[44],"reweighting.":[45],"However,":[46],"we":[47,80,192],"observed":[48],"that":[49,199,213],"hard":[53,68,98,118,161],"display":[55],"similar":[56],"leading":[58],"hard-noisy":[60],"confusion":[61,64],"issue.":[62],"Such":[63],"is":[65,111,130],"problematic":[66],"are":[70,168],"vital":[71],"for":[72,137,146],"modeling":[73],"user":[74],"preferences.":[75],"To":[76,181],"solve":[77],"this":[78],"problem,":[79],"propose":[81,193],"LLMHNI":[82,102,150,214],"framework,":[83],"leveraging":[84],"two":[85],"auxiliary":[86],"user-item":[87,104,147,157],"relevance":[88,106,148,155],"signals":[89],"generated":[90],"by":[91,189],"Large":[92],"Language":[93],"Models":[94],"(LLMs)":[95],"differentiate":[97],"samples.":[101,164],"obtains":[103],"semantic":[105],"from":[107,202],"LLM-encoded":[108,134],"embeddings,":[109,135],"which":[110],"used":[112],"negative":[114],"sampling":[115],"select":[117],"negatives":[119],"while":[120],"filtering":[121],"out":[122],"false":[124],"negatives.":[125],"An":[126],"objective":[127],"alignment":[128],"strategy":[129,198],"proposed":[131],"project":[133],"originally":[136],"general":[138],"language":[139],"tasks,":[140],"into":[141,170],"a":[142,194],"representation":[143],"space":[144],"optimized":[145],"modeling.":[149],"also":[151],"exploits":[152],"LLM-inferred":[153,166],"logical":[154],"within":[156],"interactions":[158,167,187],"These":[165],"integrated":[169],"the":[171,183],"interaction":[172],"graph":[173,195],"guide":[175],"denoising":[176,217],"with":[177],"cross-graph":[178],"contrastive":[179,196],"alignment.":[180],"eliminate":[182],"impact":[184],"of":[185],"unreliable":[186,208],"induced":[188],"LLM":[190],"hallucination,":[191],"learning":[197],"aligns":[200],"representations":[201],"randomly":[203],"edge-dropped":[204],"views":[205],"suppress":[207],"edges.":[209],"Empirical":[210],"results":[211],"demonstrate":[212],"significantly":[215],"improves":[216],"recommendation":[219],"performance.":[220]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}