MobileForge adapts Qwen3-VL-8B to 67.2% Pass@3 on AndroidWorld using only automatically generated annotation-free data via MobileGym and HiFPO, with ForgeOwl-8B reaching 77.6%.
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Mai-ui technical report: Real-world centric foundation gui agents
35 Pith papers cite this work. Polarity classification is still indexing.
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2026 35representative citing papers
DragOn provides a new drag-grounding benchmark and training dataset for GUI agents, with evaluations suggesting potential improvements on computer-use tasks.
AndroidDaily supplies 350 verifiable tasks on 94 closed-source Android apps evaluated by GRADE (87.37% human agreement), with the strongest model achieving 62% success.
ScaleWoB generates 100+ synthetic interactive GUI environments and 1000+ verifiable tasks as web pages, releasing a 120-task mobile benchmark where state-of-the-art agents achieve 27.92% success (17.82% on long-horizon tasks) versus 92.08% for humans, with synthetic results generalizing to real apps
BBCritic reframes GUI critique as continuous semantic alignment via contrastive learning in an affordance space, outperforming larger binary SOTA models on a new four-level hierarchical benchmark without extra annotations.
Presents CUActSpot benchmark and renderer-LLM data synthesis that lets a 4B model outperform larger open-source models on complex computer interactions.
GUI grounding in VLMs is bottlenecked by prefill-stage candidate selection that decoding cannot fix, so Re-Prefill uses attention to extract and re-inject target tokens for up to 4.3% gains on ScreenSpot-Pro.
OS-SPEAR is a new evaluation toolkit that tests 22 OS agents and identifies trade-offs between efficiency and safety or robustness.
FedGUI is the first comprehensive benchmark for federated GUI agents that studies cross-platform, cross-device, cross-OS, and cross-source heterogeneity, with experiments showing performance gains from cross-platform collaboration and identifying platform and OS as the most influential factors.
Android Coach improves online agent training efficiency by enabling multiple actions per state via a critic-based coach, process reward model, and group-wise advantage estimation, delivering 7.5-8.3% success rate gains and 1.4x efficiency over PPO/GRPO baselines.
VF-Coder raises GUI code success rate from 21.68% to 28.29% and visual score from 0.4284 to 0.5584 on a new 984-task benchmark by adding direct visual perception and interaction.
Introduces Active Task Driving Memory (ATMem) and STR-GRPO to move GUI agents from passive record storage to actively maintained task states, tested on a new mobile benchmark with progress and scope-aware metrics.
InnerZoom bridges cross-layer evidence in one forward pass to achieve SOTA GUI grounding accuracy on six benchmarks while cutting latency up to 31.8% versus two-pass baselines.
GUICrafter uses curriculum learning on unannotated GUI screenshots for visual grounding followed by RL calibration on limited labels to match or exceed prior GUI agents with far less annotation.
PhoneBuddy combines real-app and mock-app RL after shared SFT, raising real-phone task success from 36.67% to 45.33% and AndroidWorld from 60.3% to 83.2%.
MemGUI-Agent uses Context-as-Action (ConAct) for proactive context management in long-horizon GUI tasks, trained on the MemGUI-3K dataset to achieve top 8B-model results on MemGUI-Bench and MobileWorld.
CLI-based coding agents outperform GUI baselines on AndroidWorld and MobileWorld, with oracles reaching 88.8% and 86.3% solvability and a new CLI-Advantage suite showing CLI superiority in bulk operations, filtering, aggregation, cross-app workflows, and hidden state.
UI-KOBE constructs reusable app knowledge graphs from autonomous exploration to provide runtime guidance that improves lightweight mobile GUI agents.
MobileExplorer reduces on-device GUI agent reasoning steps and latency by 23% via parallel UI exploration, structured memory, and a two-level rollback while maintaining or improving task success rates.
AQuaUI uses adaptive quadtrees to cut visual tokens in GUI-agent LMMs by up to 29.52% at inference time while retaining 99.06% of full-token accuracy on grounding and navigation benchmarks.
MementoGUI introduces a modular memory-control framework with working and episodic memory operators that improves long-horizon GUI agent performance over history-replay and text-only baselines.
Introduces DocOS benchmark to test GUI agents on proactively locating, comprehending, and executing instructions from online documentation in interactive web settings.
Phone-use agents avoid harm more often through inability to act than through deliberate safe choices, so benchmarks must separate unsafe judgment from capability failure.
Personalized soft prompts steer VLM attention to match user-specific gaze patterns, yielding better attention alignment and click prediction in recommendation simulations.
citing papers explorer
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MobileForge: Annotation-Free Adaptation for Mobile GUI Agents with Hierarchical Feedback-Guided Policy Optimization
MobileForge adapts Qwen3-VL-8B to 67.2% Pass@3 on AndroidWorld using only automatically generated annotation-free data via MobileGym and HiFPO, with ForgeOwl-8B reaching 77.6%.
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MemGUI-Agent: An End-to-End Long-Horizon Mobile GUI Agent with Proactive Context Management
MemGUI-Agent uses Context-as-Action (ConAct) for proactive context management in long-horizon GUI tasks, trained on the MemGUI-3K dataset to achieve top 8B-model results on MemGUI-Bench and MobileWorld.