UserSimCRS v2: Simulation-Based Evaluation for Conversational Recommender Systems
Abstract
UserSimCRS v2 expands simulation-based evaluation of conversational recommender systems with improved agenda-based simulators, LLM-based simulators, broader integration, and LLM-as-a-judge evaluation tools.
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.
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