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Yurun Chen

5 accepted papers

2026

EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automation

AAAI 2026technical

To tackle increasingly complex tasks, recent research on mobile agents has shifted towards multi-agent collaboration. Current mobile multi-agent systems are primarily deployed in the cloud, leading to high latency and operational costs. A straightforward idea is to deploy a device–cloud collaborativ

Cited by 0SourcePDFScholar
2026

Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs

CVPR 2026

As multimodal LLM-driven agents advance in autonomy and generalization, traditional static datasets face inherent scalability limitations and are insufficient for fully assessing their capabilities in increasingly complex and diverse tasks. Existing studies have attempted to generate agent tasks usi

Cited by 0SourcecodeScholar
2025

ARMO: Autoregressive Rigging for Multi-Category Objects

ICCV 2025poster

Recent advancements in large-scale generative models have significantly improved the quality and diversity of 3D shape generation. However, most existing methods focus primarily on generating static 3D models, overlooking the potential dynamic nature of certain shapes, such as humanoids, animals, an…

Cited by 0SourcePDFScholar
2025

DRiVE: Diffusion-based Rigging Empowers Generation of Versatile and Expressive Characters

CVPR 2025poster

Recent advances in generative models have enabled high-quality 3D character reconstruction from multi-modal. However, animating these generated characters remains a challenging task, especially for complex elements like garments and hair, due to the lack of large-scale datasets and effective rigging…

2025

OS Agents: A Survey on MLLM-based Agents for Computer, Phone and Browser Use

ACL 2025long

The dream to create AI assistants as capable and versatile as the fictional J.A.R.V.I.S from Iron Man has long captivated imaginations. With the evolution of multi-modal large language models ((M)LLMs), this dream is closer to reality, as (M)LLM-based Agents using computers, mobile phones and web br…