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agent/papers/items/2026-2607-11185-scalecua-scaling-computer-use-agents-with-verifiable-task-synthesis-and-efficien.md
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# Paper: SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL
---
type: paper
title: "SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL"
authors: Bowen Lv, Xiao Liu, Yanyu Ren, Hanyu Lai, Bohao Jing, Hanchen Zhang, Yanxiao Zhao, Shuntian Yao, et al.
year: 2026
venue: arXiv
url: https://arxiv.org/abs/2607.11185
code_url:
source: arxiv
collected_at: 2026-07-27
published_at: 2026-07-13
updated_at: 2026-07-13
status: queued
relevance: high
topics:
- computer-use
- multi-agent
- tool-use
- workflow-agent
methods:
-
benchmarks:
-
models:
-
datasets:
- cs.AI
related_concepts:
-
related_jobs:
-
related_experiments:
-
related_projects:
-
collection_score: 13
collection_queries: web-gui-agent
---
## One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
## Why Collected
- matched queries: web-gui-agent
- inferred topics: computer-use, multi-agent, tool-use, workflow-agent
- arXiv categories: cs.AI
- collection score: 13
## Review Checklist
- Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
- Does it include a benchmark, dataset, code, or reproducible experimental setup?
- Should it be promoted from `queued` to `skimmed` or `summarized`?
## Links
- arXiv: https://arxiv.org/abs/2607.11185