arXiv Computer Vision By Jiaming Zhang, Xuan Wang, Fuyao Zhang, Yang Cao, Lingjuan Lyu, Wei Yang Bryan Lim

Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents

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The paper introduces LGWM, a decoder‑free, action‑conditioned world model that predicts the representation of the next GUI screen directly, enabling efficient verification of transitions without semantic annotation. By comparing predicted and observed representations, the model achieves high AUC scores on the RSWT‑BENCH diagnostic, outperforming existing generative world models and matching closed‑source VLMs while operating at much lower latency. The study demonstrates that world models can serve a third role—verification—by predicting in representation space rather than generating text, code, or images.

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arXiv AI
Oct 28

GUI-JEPA: Candidate-Conditioned JEPA Latents as a Fast Action Policy for Mobile GUI Agents

GUI-JEPA introduces a decoder‑free policy for mobile GUI agents that uses a Joint‑Embedding Predictive Architecture (JEPA) to generate action candidates directly in latent space. By predicting a latent representation for each candidate action, the model scores all options in a single batched pass without token decoding, dramatically reducing computation. Experiments on AndroidControl show that GUI‑JEPA is 2.8–4.0× faster than a 7B‑scale VLM agent while retaining 86–92% of its accuracy with only 6% of the parameters.

By Bingchao Wang, Yongcheng Jing, Shunyu Liu, Chengyu Wang, Jun Huang, Jie Yang, Wei Liu, Dacheng Tao