用大模型生成游戏人物对话，构建了长篇深度互动数据集。
MCPDial: A Minecraft Persona-driven Dialogue Dataset
- 用大模型从少量人工对话生成大量角色驱动的对话
- 数据集包含数百条长对话，含角色描述与功能调用指令
- 适合研究角色化对话生成与游戏AI交互
我们提出一种新方法，利用大语言模型（LLMs）生成游戏中玩家与非玩家角色（NPC）之间的角色驱动对话。以此方法为基础，我们构建了Minecraft角色驱动对话数据集（MCPDial）。基于少量专家编写的初始对话，我们采用该方法生成了数百条额外对话。每条对话均包含玩家与NPC的丰富角色描述，且对话长度可观，支持深入、持续的交互。此外，对话中还嵌入了标准函数调用（如“Call find a resource on iron ore”），增强任务导向性。最后，我们对数据集进行了定性分析，评估其质量与特征。
原文摘要 · Abstract (English)
We propose a novel approach that uses large language models (LLMs) to generate persona-driven conversations between Players and Non-Player Characters (NPC) in games. Showcasing the application of our methodology, we introduce the Minecraft Persona-driven Dialogue dataset (MCPDial). Starting with a small seed of expert-written conversations, we employ our method to generate hundreds of additional conversations. Each conversation in the dataset includes rich character descriptions of the player and NPC. The conversations are long, allowing for in-depth and extensive interactions between the player and NPC. MCPDial extends beyond basic conversations by incorporating canonical function calls (e.g. "Call find a resource on iron ore") between the utterances. Finally, we conduct a qualitative analysis of the dataset to assess its quality and characteristics.
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