# From Tapping to Hopping: Augmenting Mobile GUI Agents with App-Native Deeplinks

arXiv: https://arxiv.org/abs/2609.30887 · HTML: https://mlsanity.com/paper/2609.30887/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in GUI and mobile agents, one of 16 directions in LLM agents and tool use.
- Builds on 28 of its 47 references that are in the map.
- First posted on arXiv 25 Sep 2026.

## Placed in

- LLM agents and tool use / [GUI and mobile agents](https://mlsanity.com/agents/gui-and-mobile-agents/)

## Builds on (most cited first, 28 of 28)

- [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://mlsanity.com/paper/2402.03300/) (2024)
- [UI-TARS: Pioneering Automated GUI Interaction with Native Agents](https://mlsanity.com/paper/2501.12326/) (2025)
- [AppAgent: Multimodal Agents as Smartphone Users](https://mlsanity.com/paper/2312.13771/) (2023)
- [Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception](https://mlsanity.com/paper/2401.16158/) (2024)
- [UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning](https://mlsanity.com/paper/2509.02544/) (2025)
- [Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks](https://mlsanity.com/paper/2501.11733/) (2025)
- [AndroidLab: Training and Systematic Benchmarking of Android Autonomous Agents](https://mlsanity.com/paper/2410.24024/) (2024)
- [AutoGLM: Autonomous Foundation Agents for GUIs](https://mlsanity.com/paper/2411.00820/) (2024)
- [MAI-UI Technical Report: Real-World Centric Foundation GUI Agents](https://mlsanity.com/paper/2512.22047/) (2025)
- [Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents](https://mlsanity.com/paper/2602.16855/) (2026)
- [MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environments](https://mlsanity.com/paper/2512.19432/) (2025)
- [AppAgentX: Evolving GUI Agents as Proficient Smartphone Users](https://mlsanity.com/paper/2503.02268/) (2025)
- [UI-Venus-1.5 Technical Report](https://mlsanity.com/paper/2602.09082/) (2026)
- [Step-GUI Technical Report](https://mlsanity.com/paper/2512.15431/) (2025)
- [UltraCUA: A Foundation Model for Computer Use Agents with Hybrid Action](https://mlsanity.com/paper/2510.17790/) (2025)
- [Odysseys: Benchmarking Web Agents on Realistic Long Horizon Tasks](https://mlsanity.com/paper/2604.24964/) (2026)
- [MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents](https://mlsanity.com/paper/2509.06477/) (2025)
- [ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents](https://mlsanity.com/paper/2605.12481/) (2026)
- [Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents](https://mlsanity.com/paper/2607.28227/) (2026)
- [From Assistants to Adversaries: Exploring the Security Risks of Mobile LLM Agents](https://mlsanity.com/paper/2505.12981/) (2025)
- [AndroidDaily: A Verifiable Benchmark for Mobile GUI Agents on Real-World Closed-Source Applications](https://mlsanity.com/paper/2605.27761/) (2026)
- [MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization](https://mlsanity.com/paper/2606.19930/) (2026)
- [DroidCall: A Dataset for LLM-powered Android Intent Invocation](https://mlsanity.com/paper/2412.00402/) (2024)
- [Xiaomi-GUI-0 Technical Report](https://mlsanity.com/paper/2606.31410/) (2026)
- [PhoneBuddy: Training Open Models for Agentic Phone Use](https://mlsanity.com/paper/2606.23049/) (2026)
- [UI-Venus-2 Technical Report](https://mlsanity.com/paper/2609.00028/) (2026)
- [Enhancing GUI Exploration Coverage of Android Apps with Deep Link-Integrated Monkey](https://mlsanity.com/paper/2404.19307/) (2024)
- [KnowAct-GUIClaw: Know Deeply, Act Perfectly, Personal GUI Assistant with Self-Evolving Memory and Skill](https://mlsanity.com/paper/2607.12625/) (2026)

## Abstract (arXiv)

Mobile GUI agents complete tasks using GUI actions like taps and swipes. These actions are broadly applicable across applications, but reaching a navigation interface. A single deeplink call can replace a sequence of screen-by-screen GUI actions. We therefore introduce hybrid interaction, using deeplinks for direct navigation and GUI actions for other on-screen operations and fallback. To enable this, we discover candidate deeplinks through static analysis, validate them on real devices, and describe their observed landing screens. This process creates a verified and grounded deeplink catalog that pairs each working deeplink with a description of its landing screen. Using this catalog, we introduce GUI-Hopper, a improves task success in commercial applications on real devices, further demonstrating the benefits of hybrid interaction.