What's Missing in Screen-to-Action? Towards a UI-in-the-Loop Paradigm for Multimodal GUI Reasoning
On the map: LLM reasoning → Multimodal reasoning
Abstract (arXiv)
Existing Graphical User Interface (GUI) reasoning tasks remain challenging, particularly in UI understanding. Current methods typically rely on direct screen-based decision-making, which lacks interpretability and overlooks a comprehensive understanding of UI elements, ultimately leading to task failure. To enhance the understanding and interaction with UIs, we propose an innovative GUI reasoning paradigm called UI-in-the-Loop (UILoop). Our approach treats the GUI reasoning task as a cyclic Screen-UI elements-Action process. By enabling Multimodal Large Language Models (MLLMs) to explicitly learn the localization, semantic functions, and practical usage of key UI elements, UILoop achieves precise element discovery and performs interpretable reasoning. Furthermore, we introduce a more challenging UI Comprehension task centered on UI elements with three evaluation metrics. Correspondingly, we contribute a benchmark of 26K samples (UI Comprehension-Bench) to comprehensively evaluate existing methods' mastery of UI elements. Extensive experiments demonstrate that UILoop achieves state-of-the-art UI understanding performance while yielding superior results in GUI reasoning tasks.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 44 of its 84 references that are in the map. First posted on arXiv 8 Apr 2026.
Builds on
44 of 84 references.
Closest ancestors · 6
Same direction, newest first
- 2026MMFineReason: Closing the Multimodal Reasoning Gap via Open Data-Centric Methods29 Jan
- 2025ARM-Thinker: Reinforcing Multimodal Generative Reward Models with Agentic Tool Use and Visual Reasoning4 Dec
- 2025InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners19 Apr
- 2025UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning27 Mar
- 2025OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models22 Feb
- 2024Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction5 Dec
Other references · 38
- 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
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- 2024GPT-4o System Cardcited by 4,467
- 2024HybridFlow: A Flexible and Efficient RLHF Frameworkcited by 1,980
- 2025UI-TARS: Pioneering Automated GUI Interaction with Native Agentscited by 584
- 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agentscited by 370
- 2024WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learningcited by 243
- 2025GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agentscited by 240
- 2025Mobile-Agent-v3: Fundamental Agents for GUI Automationcited by 183
- 2020Mapping Natural Language Instructions to Mobile UI Action Sequencescited by 180
- 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
26 more
- 2024The BrowserGym Ecosystem for Web Agent Researchcited by 152
- 2024GUI Agents with Foundation Models: A Comprehensive Surveycited by 110
- 2025UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interactioncited by 68
- 2025MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agentscited by 64
- 2023DroidBot-GPT: GPT-powered UI Automation for Androidcited by 47
- 2025OS Agents: A Survey on MLLM-based Agents for General Computing Devices Usecited by 35
- 2025InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimizationcited by 24
- 2026UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervisioncited by 23
- 2026ExpSeek: Self-Triggered Experience Seeking for Web Agentscited by 23
- 2026ReCreate: Reasoning and Creating Domain Agents Driven by Experiencecited by 22
- 2025UI-E2I-Synth: Advancing GUI Grounding with Large-Scale Instruction Synthesiscited by 20
- 2026PALM: Progress-Aware Policy Learning via Affordance Reasoning for Long-Horizon Robotic Manipulationcited by 20
- 2025Make LVLMs Focus: Context-Aware Attention Modulation for Better Multimodal In-Context Learningcited by 18
- 2025Learning Human-Perceived Fakeness in AI-Generated Videos via Multimodal LLMscited by 16
- 2025VeriOS: Query-Driven Proactive Human-Agent-GUI Interaction for Trustworthy OS Agentscited by 15
- 2025TrimTokenator-LC: Towards Adaptive Visual Token Pruning for Large Multimodal Models with Long Contextscited by 14
- 2026Don't Act Blindly: Robust GUI Automation via Action-Effect Verification and Self-Correctioncited by 14
- 2026NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neuronscited by 13
- 2026AndroTMem: From Interaction Trajectories to Anchored Memory in Long-Horizon GUI Agentscited by 10
- 2026FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Modelscited by 8
- 2025Auditing Data Membership in Reinforcement Learning With Verifiable Rewardscited by 6
- 2026Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learningcited by 5
- 2026When Models Learn to Ask Why: Adaptive Causal Reasoning for Trustworthy Medical Vision-Language Modelscited by 5
- 2025Last Layer Logits to Logic: Empowering LLMs with Logic-Consistent Structured Knowledge Reasoningcited by 4
- 2026CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphscited by 3
- 2026CirrusBench: Evaluating LLM-based Agents Beyond Correctness in Real-World Cloud Service Environmentscited by 3
Built on by
Citing papers per year: 2026: 4.
4 papers.
- 2026TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrievalcited by 13
- 2026MedSynapse-V: Bridging Visual Perception and Clinical Intuition via Latent Memory Evolutioncited by 12
- 2026EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learningcited by 2
- 2026AWM: Answerable Working Memory for Long-Document VQA Agentscited by 1
- 2026AWM: Answerable Working Memory for Long-Document VQA Agents26 Aug 2026
- 2026EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning22 Aug 2026
- 2026MedSynapse-V: Bridging Visual Perception and Clinical Intuition via Latent Memory Evolution29 Apr 2026
- 2026TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval23 Apr 2026
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- 2025GUI Knowledge Bench: Revealing the Knowledge Gap of VLMs in GUI Tasks
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- 2024Read Anywhere Pointed: Layout-aware GUI Screen Reading with Tree-of-Lens Grounding
- 2024GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
- 2025A Survey on (M)LLM-Based GUI Agents
- 2026Reasoning for Mobile User Experience with Multimodal LLMs: Task, Benchmark, and Approach
- 2026GUITrans2Act: Understanding User Operational Behaviors from Mobile GUI Interactions with Vision-Language Models