Prompted LLMs as Chatbot Modules for Long Open-domain Conversation

• URL: http://arxiv.org/abs/2305.04533v1
• Date: Mon, 8 May 2023 08:09:00 GMT
• Title: Prompted LLMs as Chatbot Modules for Long Open-domain Conversation
• Authors: Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee
• Abstract summary: We propose MPC, a new approach for creating high-quality conversational agents without the need for fine-tuning. Our method utilizes pre-trained large language models (LLMs) as individual modules for long-term consistency and flexibility.
• Score: 7.511596831927614
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose MPC (Modular Prompted Chatbot), a new approach for creating high-quality conversational agents without the need for fine-tuning. Our method utilizes pre-trained large language models (LLMs) as individual modules for long-term consistency and flexibility, by using techniques such as few-shot prompting, chain-of-thought (CoT), and external memory. Our human evaluation results show that MPC is on par with fine-tuned chatbot models in open-domain conversations, making it an effective solution for creating consistent and engaging chatbots.

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