GUI 记忆别存单步也别存整轨:华为子目标记忆图,SPA-Bench +11.11%
GUI 记忆别存单步也别存整轨:华为子目标记忆图,SPA-Bench +11.11%
View PDF HTML (experimental) Abstract: GUI agents aim to automate complex user tasks by interacting with mobile interfaces, but ef- fective decision-making in long-horizon set- tings requires reusing prior experience rather than relying solely on the environment ob-...
华为子目标记忆图在SPA-Bench上提升11.11%,自动化复杂用户任务 (arXiv:2610.31307)
“View PDF HTML (experimental) Abstract: GUI agents aim to automate complex user tasks by interacting with mobile interfaces, but ef- fective”
Abstract:GUI agents aim to automate complex user tasks by interacting with mobile interfaces, but ef- fective decision-making in long-horizon set- tings requires reusing prior experience rather than relying solely on the environment ob- servations. Existing memory-based methods typically store experience either at the single- action level or as entire trajectories. Single- step actions are often too fine-grained to carry meaningful semantics, since the success of an individual action does not necessarily imply progress towards the overall goal. In contrast, whole trajectories are often too coarse-grained and difficult to reuse across different tasks. We propose a subgoal-aware memory graph that distils past trajectories into structured, reusable evidence at the level of subgoals. We define a subgoal as consecutive actions shar- ing a single intent, the granularity at which progress toward the task becomes meaning- ful. To reduce redundancy and support cross- task reuse, we organise subgoal experiences as nodes in a graph, where related memories can be merged, extended, and retrieved based on the environment observation. On SPA-Bench, our method improves success rate by 11.11% over the baseline.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.31307 [cs.AI] |
| (or arXiv:2610.31307v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.31307 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Dezhao Luo [view email]
[v1]
Thu, 22 Oct 2026 14:06:00 UTC (216 KB)
Source: Agent Control Flash News · arxiv.org
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