{
  "paper_url": "https://arxiv.org/html/2610.36877v1",
  "source_url": "https://arxiv.org/pdf/2610.36877v1#page=3",
  "figure": "Figure 2",
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  "copyright": "Original paper authors; fixed arXiv v1 license applies",
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  "caption": "Figure 2: Overview of GUI-JEPA. Top: on a real AndroidControl step, the frozen JEPA encoder embeds the screenshot once, the residual predictor turns it into one latent per candidate in a single batch, and the structural head and the text matcher score every candidate (bars: a trained base policy’s probabilities on this step; grids are schematic). Bottom: the training stages, and scoring in one pass versus decoding token by token (measured in Section 4.5 ). Circled numbers mark the stage that trains each module (1: JEPA pretraining, 2: policy training, 3: text rankers on the fixed policy); flame = trained, snowflake = frozen; green marks the recorded (correct) action.",
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