# Code2World: A GUI World Model via Renderable Code Generation

Authors: Yuhao Zheng, Li'an Zhong, Yi Wang, Rui Dai, Kaikui Liu, Xiangxiang Chu, Linyuan Lv, Philip Torr, Kevin Qinghong Lin.

Predicts a GUI's next visual state by generating renderable code, and evaluates whether the predicted outcomes help mobile-agent navigation.

First public: 2026-02-10.
ArXiv initial submission: 2026-02-10.

[Original paper](https://arxiv.org/abs/2602.09856) · [Reading-list entry](https://neural-os.com/reading-list/papers/2602.09856/)
[Preprint BibTeX](https://neural-os.com/reading-list/papers/2602.09856/citation.bib) · [Preprint CSL-JSON](https://neural-os.com/reading-list/papers/2602.09856/citation.csl.json) · [JSON record](https://neural-os.com/reading-list/papers/2602.09856/record.json)

**Contribution:** Constructs paired screen/action/code data and trains with rendered visual feedback to balance appearance and action consistency.

**Model output:** Renderable UI code, converted into the predicted next screen.

**Action interface:** A current GUI observation and a proposed interaction, represented for the model with action descriptions and visual cues.

**State and memory:** Prediction conditions on the current screen and action; renderable structure represents the output interface.

**Relationship to NeuralOS:** Code2World cites NeuralOS in Section 2.2 and its bibliography.

**Scope and limitations:** Uses generated code and a browser to predict screens for Android navigation.

[Relationship source](https://arxiv.org/html/2602.09856v1#S2.SS2)

Related terms: Code2World, GUI world model, renderable code, next-screen prediction, AndroidCode.

## Method comparisons

**Direct frame generation and renderable-code prediction**

NeuralOS predicts desktop frames using learned state and a diffusion renderer. Code2World predicts a UI through code that is then rendered into a screen, and tests its usefulness for mobile navigation. Code2World cites NeuralOS in Section 2.2.

Sources: [Original NeuralOS paper](https://arxiv.org/html/2507.08800v1) · [Code2World Section 2.2](https://arxiv.org/html/2602.09856v1#S2.SS2)

Paper details: [NeuralOS: Towards Simulating Operating Systems via Neural Generative Models](https://neural-os.com/reading-list/papers/2507.08800/) · [Code2World: A GUI World Model via Renderable Code Generation](https://neural-os.com/reading-list/papers/2602.09856/)


## Approaches

- [GUI prediction and planning](https://neural-os.com/reading-list/guides/games-to-computers/#gui-prediction-and-planning): Predict the consequences of interface actions so an agent can compare alternatives before execution. Prediction targets include textual changes, screen images, and renderable interface code.

Reading-list version 1.0.1; literature checked through 2026-10-19.