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Paper · arXiv 2605.19769

OpenComputer: Verifiable Software Worlds for Computer-Use Agents

Jinbiao Wei, Qianran Ma, Yilun Zhao, Xiao Zhou, Kangqi Ni, Guo Gan, Arman Cohan

89 upvotesMay 19, 2026arXiv 预印本
AI 摘要

OpenComputer presents a framework for creating verifiable software environments for computer-use agents through integrated state verification, self-improving layers, task synthesis, and evaluation systems across multiple desktop applications.

verifier-grounded frameworkstate verifiersself-evolving verification layertask-generation pipelineevaluation harnessdesktop applicationsmachine-checkable taskspartial-credit rewardshuman adjudicationLLM-as-judge evaluationcomputer automation

Abstract

We present OpenComputer, a verifier-grounded framework for constructing verifiable software worlds for computer-use agents. OpenComputer integrates four components: (1) app-specific state verifiers that expose structured inspection endpoints over real applications, (2) a self-evolving verification layer that improves verifier reliability using execution-grounded feedback, (3) a task-generation pipeline that synthesizes realistic and machine-checkable desktop tasks, and (4) an evaluation harness that records full trajectories and computes auditable partial-credit rewards. In its current form, OpenComputer covers 33 desktop applications and 1,000 finalized tasks spanning browsers, office tools, creative software, development environments, file managers, and communication applications. Experiments show that OpenComputer's hard-coded verifiers align more closely with human adjudication than LLM-as-judge evaluation, especially when success depends on fine-grained application state. Frontier agents struggle with end-to-end completion despite partial progress, and open-source models exhibit sharp drops from their OSWorld-Verified scores, exposing a persistent gap in robust computer automation.

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