Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances
This addresses the challenge of creating engaging conversation models for entertainment or interactive applications, but it is incremental as it builds on existing large-scale language models.
The paper tackles the problem of mimicking fictional characters in open-domain chatbots with only a few available utterances, proposing Pseudo Dialog Prompting (PDP) to generate responses that better reflect character style than baselines.
In this paper, we consider mimicking fictional characters as a promising direction for building engaging conversation models. To this end, we present a new practical task where only a few utterances of each fictional character are available to generate responses mimicking them. Furthermore, we propose a new method named Pseudo Dialog Prompting (PDP) that generates responses by leveraging the power of large-scale language models with prompts containing the target character's utterances. To better reflect the style of the character, PDP builds the prompts in the form of dialog that includes the character's utterances as dialog history. Since only utterances of the characters are available in the proposed task, PDP matches each utterance with an appropriate pseudo-context from a predefined set of context candidates using a retrieval model. Through human and automatic evaluation, we show that PDP generates responses that better reflect the style of fictional characters than baseline methods.