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LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking.

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Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation., , , , и . CoRR, (2021)GPU Accelerated Feature Engineering and Training for Recommender Systems., , , , , , , , , и . RecSys Challenge, стр. 16-23. ACM, (2020)Tutorial: Feature Engineering for Recommender Systems., , и . RecSys, стр. 754-755. ACM, (2020)Why Are Deep Learning Models Not Consistently Winning Recommender Systems Competitions Yet?, , и . Proceedings of the Recommender Systems Challenge 2020, стр. 44-49. ACM, (сентября 2020)LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking., , , , и . CoRR, (2023)Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation., , , , и . RecSys, стр. 143-153. ACM, (2021)Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS., , , , , и . KDD, стр. 3503-3504. ACM, (2020)Adapting session based recommendation for features through transfer learning.. RecSys, стр. 481. ACM, (2018)Accelerating recommender system training 15x with RAPIDS., , , , , и . RecSys Challenge, стр. 8:1-8:5. ACM, (2019)Building and Deploying a Multi-Stage Recommender System with Merlin., , , , и . RecSys, стр. 632-635. ACM, (2022)