April 16, 2024, 4:51 a.m. | Shangyu Chen, Zibo Zhao, Yuanyuan Zhao, Xiang Li

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.08692v1 Announce Type: cross
Abstract: The emergence of Large Language Models (LLMs) has innovated the development of dialog agents. Specially, a well-trained LLM, as a central process unit, is capable of providing fluent and reasonable response for user's request. Besides, auxiliary tools such as external knowledge retrieval, personalized character for vivid response, short/long-term memory for ultra long context management are developed, completing the usage experience for LLM-based dialog agents. However, the above-mentioned techniques does not solve the issue of \textbf{personalization …

abstract agent agents arxiv cs.ai cs.cl cs.ir development dialog emergence knowledge language language models large language large language models llm llms long-term memory personalized process profile request retrieval tools type

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