{"id":"https://openalex.org/W4414360047","doi":"https://doi.org/10.24963/ijcai.2025/351","title":"CLLMRec: Contrastive Learning with LLMs-based View Augmentation for Sequential Recommendation","display_name":"CLLMRec: Contrastive Learning with LLMs-based View Augmentation for Sequential Recommendation","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360047","doi":"https://doi.org/10.24963/ijcai.2025/351"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/351","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5080310406","display_name":"Fan L\u00fc","orcid":"https://orcid.org/0000-0002-4932-3850"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fan Lu","raw_affiliation_strings":["Nanjing University of Information Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Information Science and Technology","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007818509","display_name":"Xiaolong Xu","orcid":"https://orcid.org/0000-0003-4879-9803"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolong Xu","raw_affiliation_strings":["Nanjing University of Information Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Information Science and Technology","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003553958","display_name":"Haolong Xiang","orcid":"https://orcid.org/0000-0003-4565-8829"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haolong Xiang","raw_affiliation_strings":["Nanjing University of Information Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Information Science and Technology","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006514077","display_name":"Lianyong Qi","orcid":"https://orcid.org/0000-0001-9875-9856"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianyong Qi","raw_affiliation_strings":["China University of Petroleum (East China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Petroleum (East China)","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102436547","display_name":"Xiaokang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaokang Zhou","raw_affiliation_strings":["Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001996145","display_name":"Fei Dai","orcid":"https://orcid.org/0000-0001-6469-357X"},"institutions":[{"id":"https://openalex.org/I25399270","display_name":"Southwest Forestry University","ror":"https://ror.org/03dfa9f06","country_code":"CN","type":"education","lineage":["https://openalex.org/I25399270"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Dai","raw_affiliation_strings":["Southwest Forestry University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Forestry University","institution_ids":["https://openalex.org/I25399270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038791483","display_name":"Wanchun Dou","orcid":"https://orcid.org/0000-0003-4833-2023"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanchun Dou","raw_affiliation_strings":["Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5080310406"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":5.1097,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95798583,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3153","last_page":"3161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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/T10028","display_name":"Topic Modeling","score":0.9672999978065491,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9524000287055969,"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/baseline","display_name":"Baseline (sea)","score":0.4936000108718872},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.41940000653266907},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40459999442100525},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.36660000681877136},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.3564999997615814},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.3336000144481659},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.32710000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265999913215637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5806999802589417},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4936000108718872},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43220001459121704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4260999858379364},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.32710000872612},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C2777629044","wikidata":"https://www.wikidata.org/wiki/Q614959","display_name":"Contrastive analysis","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2517000138759613},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/351","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1,87,177],"generates":[2],"embedding":[3],"representations":[4],"from":[5,156],"historical":[6,23,55],"user-item":[7,24,56],"interactions":[8],"to":[9,17,46,76,122,153],"recommend":[10],"the":[11,18,48,66,91,140,167],"next":[12],"potential":[13],"interaction":[14],"item.":[15],"Due":[16],"complexity":[19],"and":[20,44,51,68,125,134,174],"variability":[21],"of":[22,71],"interactions,":[25,57],"extracting":[26,58],"effective":[27,60,144],"user":[28,61,81,127],"features":[29],"is":[30],"quite":[31],"challenging.":[32],"Recent":[33],"studies":[34],"have":[35],"employed":[36],"sequential":[37],"networks":[38,43],"such":[39],"as":[40],"time":[41],"series":[42],"Transformers":[45],"capture":[47,77],"intricate":[49],"dependencies":[50],"temporal":[52],"patterns":[53],"in":[54,80,85,109,150],"more":[59],"features.":[62],"However,":[63],"limited":[64],"by":[65],"scarcity":[67],"suboptimal":[69],"quality":[70],"data,":[72],"these":[73],"methods":[74],"struggle":[75],"subtle":[78,148],"differences":[79,108,149],"sequences,":[82],"which":[83,105],"results":[84,160],"diminished":[86],"accuracy.":[88],"To":[89],"address":[90],"above":[92],"issue,":[93],"we":[94],"propose":[95],"a":[96],"contrastive":[97,145],"learning":[98],"framework":[99],"with":[100],"LLMs-based":[101],"view":[102],"augmentation":[103],"(CLLMRec),":[104],"effectively":[106],"mines":[107],"behavioral":[110,151],"sequences":[111,152],"through":[112],"sample":[113],"generation.":[114],"Specifically,":[115],"CLLMRec":[116,138],"utilizes":[117],"LLMs":[118],"(Large":[119],"Language":[120],"Models)":[121],"augment":[123],"views":[124,142],"expand":[126],"behavior":[128],"sequence":[129],"representations,":[130],"providing":[131],"high-quality":[132],"positive":[133],"negative":[135],"samples.":[136],"Subsequently,":[137],"employs":[139],"augmented":[141],"for":[143],"learning,":[146],"capturing":[147],"suppress":[154],"interference":[155],"irrelevant":[157],"noise.":[158],"Experimental":[159],"on":[161],"three":[162],"public":[163],"datasets":[164],"demonstrate":[165],"that":[166],"proposed":[168],"method":[169],"outperforms":[170],"state-of-the-art":[171],"baseline":[172],"models,":[173],"significantly":[175],"enhances":[176],"performance.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}