1 citations · 2 across the 8 of their papers we have counts for
9 papers
When Does Language Matter? Multilingual Instructions Reveal Step-wise Language Sensitivity in Vision-Language-Action Models
Xuan Dong, Zhe Han, Tianhao Niu +2
Vision-Language-Action (VLA) models have shown strong performance in language-conditioned robotic manipulation, yet their robustness to linguistic variation remains poorly understo…
EpiBench: Benchmarking Multi-turn Research Workflows for Multimodal Agents
Xuan Dong, Huanyang Zheng, Tianhao Niu +7
Scientific research follows multi-turn, multi-step workflows that require proactively searching the literature, consulting figures and tables, and integrating evidence across paper…
MiroFlow: Towards High-Performance and Robust Open-Source Agent Framework for General Deep Research Tasks
Shiqian Su, Sen Xing, Xuan Dong +13
Despite the remarkable progress of large language models (LLMs), the capabilities of standalone LLMs have begun to plateau when tackling real-world, complex tasks that require inte…
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
MiroMind Team, Song Bai, Lidong Bing +52
We present MiroThinker v1.0, an open-source research agent designed to advance tool-augmented reasoning and information-seeking capabilities. Unlike previous agents that only scale…
ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data
Zhaoyang Liu, Jingjing Xie, Zichen Ding +27
Vision-Language Models (VLMs) have enabled computer use agents (CUAs) that operate GUIs autonomously, showing great potential, yet progress is limited by the lack of large-scale, o…
MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
Xuehui Wang, Zhenyu Wu, JingJing Xie +25
We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms. It comprises four levels: GUI…
ZeroGUI: Automating Online GUI Learning at Zero Human Cost
Chenyu Yang, Shiqian Su, Shi Liu +11
The rapid advancement of large Vision-Language Models (VLMs) has propelled the development of pure-vision-based GUI Agents, capable of perceiving and operating Graphical User Inter…
PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models
Chenyu Yang, Xuan Dong, Xizhou Zhu +7
Large Vision-Language Models (VLMs) have been extended to understand both images and videos. Visual token compression is leveraged to reduce the considerable token length of visual…
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
Chenyu Yang, Xizhou Zhu, Jinguo Zhu +9
Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data. Despite these advances, there is…