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#computer vision Preprint Oct 2026

OpenMobile-2: Building Versatile Mobile Agents with Scalable Environments and App-Native Tools

We introduce OpenMobile-2, a near-frontier mobile agent with fully open training environments and recipes. We make three key advances: (1) Diverse environments with simulated commercial apps: We build MobileGym++, featuring 35 realistic, functionally rich commercial-style apps with cross-app workflows, while preserving...

Chen-Yang Yan, Ying-Ying Zhang, Kanzhi Cheng et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Glasseek: A Transparent Recipe for Training and Trustworthy Evaluation of DeepSearch Agents

Deep search enables language agents to solve complex information-seeking tasks through iterative web exploration. However, developing robust open-source agents remains challenging for three reasons. First, opaque trajectory-construction pipelines make training data difficult to audit and reproduce. Second, context comp...

Cong Pang, Jia-Qi Su, Cheng-Rui Wu et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Branching On-Policy Distillation

On-policy distillation (OPD) provides teacher supervision on student-generated trajectories, but a single trajectory realizes only one continuation at each decision, limiting supervision coverage under a finite sampling budget. We propose BranchOPD (Branching On-Policy Distillation), which selects informative decision...

Dong-Yang Chen, Shudong Liu, Shu-Bo Li et al. · 0 citations
Preprint Aug 2026

OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories

Visual tool use has emerged as a fundamental capability for multimodal agents to actively acquire evidence beyond a fixed image encoding. The prevailing recipe learns this capability from teacher-generated trajectories filtered for answer correctness, implicitly assuming that every successful demonstration provides eff...

Changhao Xiang, Shi-Lin Zhang, Zheng Ma et al. · 1 citation
Preprint Aug 2026

Paint What You See: Benchmarking Dexterous Visual Tool Use in Multimodal Agents

EASEL is proposed, a benchmark evaluating a controlled instance of dexterous visual tool use that adopts reference-guided visual reconstruction as its primary proxy task: the agent incrementally paints a canvas to match a reference image.

Shudong Liu, Dong-Yang Chen, En-Ci Zhang et al. · 0 citations

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