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ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation.

, , , , , , , , and . WWW, page 3497-3508. ACM, (2024)

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How Can Recommender Systems Benefit from Large Language Models: A Survey., , , , , , , , , and 1 other author(s). CoRR, (2023)Vector Quantization for Recommender Systems: A Review and Outlook., , , , , , , , and . CoRR, (2024)QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback., , , , , , , , and . CoRR, (2021)DFFM: Domain Facilitated Feature Modeling for CTR Prediction., , , , , , , , and . CIKM, page 4602-4608. ACM, (2023)AutoGen: An Automated Dynamic Model Generation Framework for Recommender System., , , , , , , , and . WSDM, page 598-606. ACM, (2023)SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data., , , , , , , , , and 1 other author(s). Briefings Bioinform., (September 2023)Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning., , , , , and . IEEE Trans. Knowl. Data Eng., 35 (4): 4018-4032 (April 2023)ALT: Towards Fine-grained Alignment between Language and CTR Models for Click-Through Rate Prediction., , , , , , , and . CoRR, (2023)ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation., , , , , , , , and . CoRR, (2023)AIM: Automatic Interaction Machine for Click-Through Rate Prediction., , , , , , , and . CoRR, (2021)