A Task-State Representation for Long-Horizon Mobile GUI Agents
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Computer Science > Computation and Language
Title:A Task-State Representation for Long-Horizon Mobile GUI Agents
Abstract:While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient screen observations. As execution histories grow, this entanglement imposes a severe context burden, causing agents to forget initial requirements, hallucinate progress, or repeatedly interact with stale interfaces. To address this, we introduce Task-State Representation (TSR), a training-free framework that explicitly decouples task state from sensory input. Acting as a lightweight external wrapper, TSR maintains three structured components: a global instruction summary, a dynamic progress tracker for subgoals, and a transition-aware action verifier. By continuously updating through pre- and post-action visual comparisons, TSR effectively guides the agent's reasoning without requiring architectural modifications. Experiments across four mobile GUI benchmarks validate TSR's effectiveness, yielding up to a 12 absolute point increase in success rate on complex cross-application and memory-intensive tasks.
| Comments: | Preprint. 9 pages, 3 figures |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2607.00502 [cs.CL] |
| (or arXiv:2607.00502v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2607.00502
arXiv-issued DOI via DataCite (pending registration)
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