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cs.CV2025
PixelRefer: A Unified Framework for Spatio-Temporal Object Referring with Arbitrary Granularity
Yuqian Yuan, Wenqiao Zhang, Xin Li +6
Multimodal large language models (MLLMs) have demonstrated strong general-purpose capabilities in open-world visual comprehension. However, most existing MLLMs primarily focus on h…
cs.CV2025
RynnVLA-001: Using Human Demonstrations to Improve Robot Manipulation
Yuming Jiang, Siteng Huang, Shengke Xue +10
This paper presents RynnVLA-001, a vision-language-action(VLA) model built upon large-scale video generative pretraining from human demonstrations. We propose a novel two-stage pre…
cs.CV2025
RynnEC: Bringing MLLMs into Embodied World
Ronghao Dang, Yuqian Yuan, Yunxuan Mao +6
We introduce RynnEC, a video multimodal large language model designed for embodied cognition. Built upon a general-purpose vision-language foundation model, RynnEC incorporates a r…