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20242026
most citedOS-Copilot: Towards Generalist Computer Agents with Self-Improvement

5 citations · 10 across the 26 of their papers we have counts for

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13 papers · 1 filter

cs.AI2026

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

Qiushi Sun, Kanzhi Cheng, Yian Wang +20

Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Verifying whether it fulfilled the…

cs.AI2026

AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities

Kai Chen, Zichen Ding, Jiaye Ge +20

As Large Language Models (LLMs) evolve into autonomous agents, the need for unified evaluation infrastructure becomes critical. However, current evaluation pipelines remain highly…

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

OpenMobile: Building Open Mobile Agents with Task and Trajectory Synthesis

Kanzhi Cheng, Zehao Li, Zheng Ma +11

Mobile agents powered by vision-language models have demonstrated impressive capabilities in automating mobile tasks, with recent leading models achieving a marked performance leap…

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.AI2026

TIDE: Trajectory-based Diagnostic Evaluation of Test-Time Improvement in LLM Agents

Hang Yan, Xinyu Che, Fangzhi Xu +7

Recent advances in autonomous LLM agents demonstrate their ability to improve performance through iterative interaction with the environment. We define this paradigm as Test-Time I…

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…

cs.AI2025

OS-Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows

Qiushi Sun, Mukai Li, Zhoumianze Liu +11

Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobile platforms. While these agents…

cs.AI2025

ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

Qiushi Sun, Zhoumianze Liu, Chang Ma +18

Large Language Models (LLMs) have extended their impact beyond Natural Language Processing, substantially fostering the development of interdisciplinary research. Recently, various…

cs.AI2025

Breaking the Data Barrier -- Building GUI Agents Through Task Generalization

Junlei Zhang, Zichen Ding, Chang Ma +4

Graphical User Interface (GUI) agents offer cross-platform solutions for automating complex digital tasks, with significant potential to transform productivity workflows. However,…

cs.AI2024

OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis

Qiushi Sun, Kanzhi Cheng, Zichen Ding +12

Graphical User Interface (GUI) agents powered by Vision-Language Models (VLMs) have demonstrated human-like computer control capability. Despite their utility in advancing digital…

cs.AI2024

SEAGraph: Unveiling the Whole Story of Paper Review Comments

Jianxiang Yu, Jiaqi Tan, Zichen Ding +7

Peer review, as a cornerstone of scientific research, ensures the integrity and quality of scholarly work by providing authors with objective feedback for refinement. However, in t…

cs.AI2024★ 5 cited

OS-Copilot: Towards Generalist Computer Agents with Self-Improvement

Zhiyong Wu, Chengcheng Han, Zichen Ding +5

Autonomous interaction with the computer has been a longstanding challenge with great potential, and the recent proliferation of large language models (LLMs) has markedly accelerat…