activity
20242026
most citedAgent S: An Open Agentic Framework that Uses Computers Like a Human

2 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Neuro-Symbolic Computer Use: Learning Reusable Policies for Reliable and Efficient Execution

Hyewon Suh, Thanh Minh Nguyen, Chih-Lun Lee +5

Many computer tasks recur: the same workflow runs many times, with new inputs and from different starting states. Current computer-use agents re-plan every step of every run, which…

cs.AI2026

Stateful Reasoning via Insight Replay

Bin Lei, Caiwen Ding, Jiachen Yang +2

Chain-of-Thought (CoT) reasoning has become a foundation for eliciting multi-step reasoning in large language models, but recent studies show that its benefits do not scale monoton…

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.AI2025

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

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★ 2 cited

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…