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Adapting Large Language Models for Recommendation (LLM4Rec) has shown promising results.
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How Can Recommender Systems Benefit from Large Language Models: A Survey
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LLMRec: Benchmarking Large Language Models on Recommendation Task
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Towards Language Models that can See: Computer Vision through the Lens of Natural Language
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PALR: Personalization Aware LLMs for Recommendation
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Recommender Systems in the Era of Large Language Models
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A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage
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LLaMA: Open and Efficient Foundation Language Models
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Zero-Shot Next-Item Recommendation using Large Pretrained Language Models
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A Survey on Large Language Models for Recommendation
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Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models
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Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
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A Survey on Incremental Update for Neural Recommender Systems
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CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation
Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, and Xiangnan He. 2023b · 2023
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Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
Yang Zhang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, and Xiangnan He. 2024 · 2024
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