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Personalized LLM Response Generation with Parameterized Memory Injection
April 5, 2024, 4:47 a.m. | Kai Zhang, Lizhi Qing, Yangyang Kang, Xiaozhong Liu
cs.CL updates on arXiv.org arxiv.org
Abstract: Large Language Models (LLMs) have exhibited remarkable proficiency in comprehending and generating natural language. On the other hand, personalized LLM response generation holds the potential to offer substantial benefits for individuals in critical areas such as medical. Existing research has explored memory-augmented methods to prompt the LLM with pre-stored user-specific knowledge for personalized response generation in terms of new queries. We contend that such paradigm is unable to perceive fine-granularity information. In this study, we …
abstract arxiv benefits cs.cl language language models large language large language models llm llms medical memory natural natural language personalized prompt research type
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