From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models. (arXiv:2401.02777v2 [cs.CL] UPDATED)

This paper introduces RAISE (Reasoning and Acting through Scratchpad and
Examples), an advanced architecture enhancing the integration of Large Language
Models (LLMs) like GPT-4 into conversational agents. RAISE, an enhancement of
the ReAct framework, incorporates a dual-component memory system, mirroring
human short-term and long-term memory, to maintain context and continuity in
conversations. It entails a comprehensive agent construction scenario,
including phases like Conversation Selection, Scene Extraction, CoT Completion,
and Scene Augmentation, leading to the LLMs Training phase. This approach
appears …

acting advanced agent agents architecture arxiv conversational conversational agents cs.cl examples fine-tuning framework gpt gpt-4 human integration language language models large language large language models llm llms memory paper raise react reasoning through