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The paper introduces the LaMP benchmark, which focuses on the personalization of large language models (LLMs) to enhance their ability to generate tailored responses. It comprises seven personalized tasks across text classification and generation, utilizing retrieval augmentation methods to improve model outputs based on user profiles. The benchmark aims to address the gap in existing NLP evaluations that typically adopt a

Author

lr54suxgb

Language

EN