TL;DR
CutVerse introduces a comprehensive benchmark for evaluating autonomous GUI agents in professional media post-production tasks, highlighting current limitations and guiding future research in complex, multimodal workflows.
Contribution
The paper presents a new benchmark with expert demonstrations and a parser for structured evaluation of GUI agents in media editing, addressing a gap in autonomous agent capabilities.
Findings
Existing agents achieve only 36.0% success on complex tasks
Current models show promise in spatial grounding and multimodal alignment
Long-horizon reliability remains a significant challenge
Abstract
While GUI agents have made significant progress in web navigation and basic operating system tasks, their capabilities in professional creative workflows remain largely underexplored. To bridge this gap, we introduce Cutverse, a benchmark designed to systematically evaluate autonomous GUI agents in realistic media post-production environments. We curate expert demonstrations across 7 professional applications (e.g., Premiere Pro, Photoshop), covering 186 complex, long-horizon tasks grounded in authentic editing workflows, involving dense multimodal interfaces and tightly coupled interaction sequences. To support scalable evaluation, we develop a lightweight parser that transforms raw screen recordings and low-level interaction logs into structured, compositional GUI action trajectories with precise grounding. Extensive evaluations reveal that existing agents achieve only 36.0\% task…
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