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MintAct: A Unified Visual Agent for Digital Environments

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

We present MintAct, a family of vision-language models that unifies UI grounding, multi-step navigation across mobile, desktop, and web, and visual tool use, trained at 2B, 4B, and 8B scales. Through careful design of our environments, data, and training recipes, MintAct models match the performance of per-domain specialists across all of these capabilities. To enable this, we develop a scalable environment and reinforcement learning (RL) infrastructure. On the environment side, we host hundreds of concurrent instances across heterogeneous per-domain backends, serving both trajectory data coll

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Evidence & attribution

First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.