arXiv:2607. 28645v1 Announce Type: cross Abstract: Recent multimodal large language models can convert visual designs directly into executable code, but real mobile products require multiple screenshots to become a buildable codebase with shared components and working navigation.
arXiv:2608. 05891v1 Announce Type: new Abstract: Mobile GUI agents can operate apps through pixel perception and touch actions, making them a promising interface for collecting and improving long-horizon mobile interaction policies.
arXiv:2607. 06306v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated growing competence in web page generation.
Large language models (LLMs) have demonstrated growing competence in web page generation. However, existing text-driven approaches rely on complex prompts that impose substantial demands on users and offer limited expressivity for page layout and cross-page visual coherence.
arXiv:2607. 28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cross-platform scalability.
arXiv:2606. 13192v1 Announce Type: new Abstract: User experience (UX) centered on usability, perceived consistency, and functional clarity is fundamental to real-world user interfaces (UI).
arXiv:2606. 01869v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly asked not only to write static interfaces, but to construct executable interactive worlds from natural language.
arXiv:2605. 26144v2 Announce Type: replace-cross Abstract: We present VISTA (VIsual Spec-To-App Benchmark), a benchmark for evaluating the end-to-end web-app generation capabilities of LLM-based agents.
arXiv:2606. 00154v1 Announce Type: cross Abstract: Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyzing a new paradigm for front-end development.
arXiv:2512. 12634v4 Announce Type: replace Abstract: Mobile GUI Agents, AI agents capable of interacting with mobile applications on behalf of users, have the potential to transform human computer interaction.
arXiv:2607. 13465v1 Announce Type: cross Abstract: LLM-based agents have rapidly improved at operating individual digital environments such as mobile applications, desktop systems, and smart homes.
arXiv:2605. 29486v2 Announce Type: replace-cross Abstract: A central bottleneck for phone-use agents is that controllable, reproducible environments covering real mobile behavior are hard to build at scale.
arXiv:2605. 25160v2 Announce Type: replace Abstract: GUI agents powered by large language models are advancing rapidly, creating urgent needs for evaluation and training based on realistic environments.