arXiv — NLP / Computation & Language · · 3 min read

VISTA: A Versatile Interactive User Simulation Toolkit for Agent Evaluation

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Computer Science > Computation and Language

arXiv:2606.11079 (cs)
[Submitted on 9 Jun 2026]

Title:VISTA: A Versatile Interactive User Simulation Toolkit for Agent Evaluation

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Abstract:Evaluation remains a critical bottleneck for interactive agent development. Existing evaluation methods often rely on static benchmarks, which fail to capture the dynamic, multi-step nature of agentic behavior and struggle to expose meaningful failure modes. While user-simulation-based evaluation offers a promising alternative, existing simulation frameworks suffer from two major limitations. First, they provide limited mechanisms for evaluating the quality and comprehensiveness of simulated interactions, making it difficult to assess whether a simulator sufficiently explores an agent's capabilities and failure modes. Second, most frameworks are restricted to either UI-only actions or API-only actions, limiting their ability to model the full range of realistic user behaviors. To address these limitations, we propose VISTA, a Versatile Interactive user Simulation Toolkit for Agent evaluation. Our toolkit includes a suite of six metrics for measuring the realism, capability coverage, and interaction effectiveness of simulated interactions. In addition, we develop a hybrid user simulator that integrates both UI-based interactions and API-based interactions, enabling more realistic and comprehensive evaluation across diverse interactive environments. We evaluate VISTA in e-commerce shopping and education customer service settings and demonstrate that it produces more realistic and comprehensive evaluations than existing methods.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2606.11079 [cs.CL]
  (or arXiv:2606.11079v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2606.11079
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Yunan Lu [view email]
[v1] Tue, 9 Jun 2026 16:39:32 UTC (4,676 KB)
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