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Prompting Large Language Models for Recommender Systems: A Comprehensive Framework and Empirical Analysis.

, , , , , , and . CoRR, (2024)

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Supervised Hierarchical Cross-Modal Hashing., , , , , and . SIGIR, page 725-734. ACM, (2019)Tweet Timeline Generation via Graph-Based Dynamic Greedy Clustering., , , , and . AIRS, volume 9460 of Lecture Notes in Computer Science, page 304-316. Springer, (2015)Bayesian Probabilistic Multi-Topic Matrix Factorization for Rating Prediction., , , and . IJCAI, page 3910-3916. IJCAI/AAAI Press, (2016)Learning Distributed Representations for Recommender Systems with a Network Embedding Approach., , and . AIRS, volume 9994 of Lecture Notes in Computer Science, page 224-236. Springer, (2016)Generating Long and Coherent Text with Multi-Level Generative Adversarial Networks., , , and . APWeb/WAIM (2), volume 12859 of Lecture Notes in Computer Science, page 49-63. Springer, (2021)MVP: Multi-task Supervised Pre-training for Natural Language Generation., , , and . ACL (Findings), page 8758-8794. Association for Computational Linguistics, (2023)Generating Long and Informative Reviews with Aspect-Aware Coarse-to-Fine Decoding., , , and . ACL (1), page 1969-1979. Association for Computational Linguistics, (2019)A Correlated Topic Model Using Word Embeddings., , , , and . IJCAI, page 4207-4213. ijcai.org, (2017)A Relevant and Diverse Retrieval-enhanced Data Augmentation Framework for Sequential Recommendation., , , and . CIKM, page 2923-2932. ACM, (2022)Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation., , , , and . CIKM, page 2442-2451. ACM, (2023)