cotomi Act: Learning to Automate Work by Watching You
Abstract
What if a browser agent could learn your work simply by watching you do it? We present cotomi Act, a browser-based computer-using agent that combines reliable multi-step task execution with persistent organizational knowledge learned from user behavior. For execution, an agent scaffold with adaptive lazy observation, verbal-diff-based history compression, coarse-grained actions, and test-time scaling via best-of-N action selection achieves 80.4% on the 179-task WebArena human-evaluation subset, exceeding the reported 78.2% human baseline. For organizational knowledge, a behavior-to-knowledge pipeline passively observes the user's browsing and progressively abstracts it into artifacts (task boards, wiki) exposed through a shared workspace editable by both user and agent. A controlled proxy evaluation confirms that task success improves as behavior-derived knowledge accumulates. In our live demonstration, attendees interact with the system in a real browser, issuing tasks and observing end-to-end autonomous execution and shared knowledge management.
Cite
@article{arxiv.2605.03231,
title = {cotomi Act: Learning to Automate Work by Watching You},
author = {Masafumi Oyamada and Kunihiro Takeoka and Kosuke Akimoto and Ryoma Obara and Masafumi Enomoto and Haochen Zhang and Daichi Haraguchi and Takuya Tamura},
journal= {arXiv preprint arXiv:2605.03231},
year = {2026}
}
Comments
7 pages, 4 figures. ACM CAIS 2026 (System Demonstrations)