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arXiv · 2305.04533

Prompted LLMs as Chatbot Modules for Long Open-domain Conversation

Gibbeum Lee·Volker Hartmann·Jongho Park·Dimitris Papailiopoulos·Kangwook Lee
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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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Gibbeum Lee, Volker Hartmann, Jongho Park, Dimitris Papailiopoulos, Kangwook Lee. 2023-05-08. Prompted LLMs as Chatbot Modules for Long Open-domain Conversation. https://doi.org/10.18653/v1/2023.findings-acl.277

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