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From the 2 of 11 linked papers with an AI index.

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cs.AI2026

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models

Qiushi Sun, Kanzhi Cheng, Yian Wang +20

The paper introduces OSReward, a benchmark for evaluating vision-language model judges that assess computer-using agent trajectories, and presents open reward models (OS‑Shepherd)…

cs.AI2026

AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities

Kai Chen, Zichen Ding, Jiaye Ge +22

The paper presents AgentCompass, an open‑source infrastructure that standardizes and simplifies the evaluation of large‑language‑model based autonomous agents by separating benchma…

cs.AI2026

MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop

Yikun Fu, Bowen Fu, Zhenyu Wu +10

Computer use agents (CUAs) have advanced rapidly in desktop automation, and a growing number of users deploy CUAs such as OpenClaw on Mac Mini for always-on automation. However, ex…

cs.AI2026

OS-Themis: A Scalable Critic Framework for Generalist GUI Rewards

Zehao Li, Zhenyu Wu, Yibo Zhao +11

Reinforcement Learning (RL) has the potential to improve the robustness of GUI agents in stochastic environments, yet training is highly sensitive to the quality of the reward func…

cs.AI2025

OS-Oracle: A Comprehensive Framework for Cross-Platform GUI Critic Models

Zhenyu Wu, Jingjing Xie, Zehao Li +8

With VLM-powered computer-using agents (CUAs) becoming increasingly capable at graphical user interface (GUI) navigation and manipulation, reliable step-level decision-making has e…