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

Understand

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 to enhance agent controllability and adaptability in complex, multi-turn dialogues.