Resources for simulation-based evaluation of conversational recommender systems (CRSs) are scarce. The UserSimCRS toolkit was introduced to address this gap. In this work, we present UserSimCRS v2, a significant upgrade aligning the toolkit with state-of-the-art research. Key extensions include an enhanced agenda-based user simulator, introduction of large language model-based simulators, integration for a wider range of CRSs and datasets, and new LLM-as-a-judge evaluation utilities. We demonstrate these extensions in a case study.

翻译：面向对话推荐系统（CRS）的基于仿真的评估资源较为稀缺。UserSimCRS工具包正是为填补这一空白而引入。本研究提出了UserSimCRS v2，这是一个与前沿研究接轨的重大升级版本。其核心扩展包括：一个增强的基于议程的用户模拟器、基于大语言模型的模拟器的引入、对更广泛CRS模型与数据集的集成支持，以及新的大语言模型即评判员评估工具。我们通过一项案例研究展示了这些扩展功能。