Paper Detail

One Rollout Is All You Get: Fully Test-Time Adaptation for GUI Agents

Ziqiang Wang, Li Gu, Zhixiang Chi, Linlian Jiang, Zihuan Jiang, Linqiang Guo, Siobhan Reid, Zhi Liu, Yang Wang

arxiv Score 23.5

Published 2026-09-28 · First seen 2026-10-02

Research Track B · General AI

Abstract

GUI agents are deployed with frozen weights and discard everything they experience on the job. Existing ways to update an agent's weights assume something deployment withholds: ground truth, rollouts beyond the single attempt (retries, samples, practice runs), or a learning phase other than deployment. Because GUI actions can be irreversible, a deployed agent gets one attempt per task occurrence, in arrival order, and every attempt counts. No ground truth is available at any point. We define fully test-time adaptation for GUI agents by these constraints and pair it with a minimal weight-space method, SOLO. Auxiliary models read each episode: a judge selects the episodes it deems successful, and a proposer-verifier pair relabels a failed episode's prefix with the subtask that prefix completed. Admitted episodes enter a short sliding window, and each admission updates a small adapter by top-K self-distillation on the agent's own predictions, provided the window holds a judged success. On recurring task streams built from WebArena, VisualWebArena and MobileWorld, SOLO improves on the frozen agent with both UI-TARS-7B and Qwen3-VL-8B, by three to six points of success rate, and exceeds two in-setting memory methods on the web streams.

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BibTeX

@article{wang2026one,
  title = {One Rollout Is All You Get: Fully Test-Time Adaptation for GUI Agents},
  author = {Ziqiang Wang and Li Gu and Zhixiang Chi and Linlian Jiang and Zihuan Jiang and Linqiang Guo and Siobhan Reid and Zhi Liu and Yang Wang},
  year = {2026},
  abstract = {GUI agents are deployed with frozen weights and discard everything they experience on the job. Existing ways to update an agent's weights assume something deployment withholds: ground truth, rollouts beyond the single attempt (retries, samples, practice runs), or a learning phase other than deployment. Because GUI actions can be irreversible, a deployed agent gets one attempt per task occurrence, in arrival order, and every attempt counts. No ground truth is available at any point. We define ful},
  url = {https://arxiv.org/abs/2609.34321},
  keywords = {cs.LG},
  eprint = {2609.34321},
  archiveprefix = {arXiv},
}

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