From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models

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 conversational conversational agents cs.ai cs.cl examples fine-tuning framework gpt gpt-4 human integration language language models large language large language models llm llms long-term memory paper raise react reasoning through