Prompt Framework for Role-playing: Generation and Evaluation

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View a PDF of the paper titled Prompt Framework for Role-playing: Generation and Evaluation, by Xun Liu and 1 other authors

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Abstract:Large language models (LLMs) exhibit impressive proficiency in natural language generation, understanding user instructions, and emulating human-like language use, which has led to significant interest in their application to role-playing scenarios. However, the manual collection of role-specific script data and the evaluation of model performance are resource-intensive processes. This project introduces a prompt-based framework designed to leverage GPT’s capabilities for the generation of role-playing dialogue datasets and the evaluation of role-playing performance. To validate the effectiveness of the GPT-based generation and evaluation, we further incorporate the recall-oriented Rouge-L metric, providing an additional quantitative measure of performance.

Submission history

From: Xun Liu [view email]
[v1]
Sun, 2 Jun 2024 06:09:56 UTC (403 KB)
[v2]
Fri, 22 Nov 2024 06:19:35 UTC (393 KB)
[v3]
Fri, 29 Nov 2024 05:05:13 UTC (393 KB)



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