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From the 2 of 8 linked papers with an AI index.

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20242026
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cs.AI2026

OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks

Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33

The paper presents OSWorld 2.0, a benchmark consisting of 108 long‑horizon, real‑world computer‑use workflows designed to evaluate how well AI agents can handle complex, multi‑step…

cs.AI2026

On the Reliability of Computer Use Agents

Gonzalo Gonzalez-Pumariega, Saaket Agashe, Jiachen Yang +2

Computer-use agents have rapidly improved on real-world tasks such as web navigation, desktop automation, and software interaction, in some cases surpassing human performance. Yet…

cs.AI2026

Scaling Agents for Computer Use

Gonzalo Gonzalez-Pumariega, Vincent Tu, Chih-Lun Lee +3

Computer-use agents (CUAs) hold promise for automating everyday digital tasks, but their performance on long-horizon, complex problems remains unreliable. Single-rollout execution…

cs.AI2025

Agents of Change: Self-Evolving LLM Agents for Strategic Planning

Nikolas Belle, Dakota Barnes, Alfonso Amayuelas +3

We address the long-horizon gap in large language model (LLM) agents by enabling them to sustain coherent strategies in adversarial, stochastic environments. Settlers of Catan prov…

cs.AI2025

Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents

Saaket Agashe, Kyle Wong, Vincent Tu +3

Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance…

cs.AI2024

Agent S: An Open Agentic Framework that Uses Computers Like a Human

Saaket Agashe, Jiuzhou Han, Shuyu Gan +3

We present Agent S, an open agentic framework that enables autonomous interaction with computers through a Graphical User Interface (GUI), aimed at transforming human-computer inte…